Book of Abstracts

Advancing Sustainable Fructose Syrup Production from Sweet Sorghum

Abdulkareem Abubakar — Department Of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria

Alhaji Zanna Umara — Ahmadu Bello University, Zaria

Suleiman Shuwa — Department Of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria

Muhammad Bashir Tijjani — Department Of Microbiology, Ahmadu Bello University, Zaria, Nigeria

Suleiman Yunusa — Department Of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria And Department Of Chemical Engineering, Nasarawa State University, Keffi, Nigeria

Toyese Oyegoke — Department Of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria And Department Of Chemical Engineering, Nasarawa State University, Keffi, Nigeria

Alewo Opuada Ameh — Department Of Chemical Engineering, Federal University, Wukari, Nigeria

The increasing need for high-fructose syrup, coupled with the need to reduce dependence on imported sweeteners and conventional corn-based production, has intensified interest in alternative renewable feedstocks. This paper evaluates the potential of sweet sorghum along side cassava, sweet potato, and plantain as sustainable feed stocks for fructose syrup production, with particular emphasis on clarification technologies, catalytic conversion pathways, and process optimization strategies. The physico-chemical characteristics of these feedstocks, juice extraction and clarification methods. The paper concludes that the feed stocks reviewed, sweet sorghum demonstrates significant potential because of its high fermentable sugar content, relatively low agricultural input requirements, adaptability to semi-arid environments, and suitability for decentralized processing. Cassava, sweet potato, and plantain also offer complementary opportunities through the valorization of surplus, non-marketable, and post-harvest biomass.

Keywords Fructose syrup Green chemistry Sweet-sorghum Sustainability.

Biodegradable Structure-Directing Agents for Sustainable Synthesis of ZSM-5 Zeolite: A Review of Amino-Acid and Biopolymers Routes

Emmanuel John — Ahmadu Bello University

Abdulazeez Yusuf Atta — Ahmadu Bello University

Baba Jibril El-yakubu — Ahmadu Bello University

Ajayi Olusegun Ayoola — Ahmadu Bello University

Abdulrauf Onimisi Ibrahim — Ahmadu Bello University

Zeolite Socony Mobil–5 (ZSM-5), a high-silica MFI-type molecular sieve, is central to downstream petroleum processing, catalytic cracking, and environmental remediation. Its conventional hydrothermal synthesis depends on quaternary-ammonium organic structure-directing agents (OSDAs) such as tetrapropylammonium hydroxide and bromide, which are costly, toxic, and release hazardous gases during template removal by calcination. These drawbacks, together with Nigeria’s heavy reliance on imported catalysts, motivate the search for greener alternatives. This review examines biodegradable structure-directing agents—amino acids (L-arginine, glycine), organic acids (citric and lactic acid), and biopolymers such as chitosan—for the synthesis of ZSM-5 and related zeolites. Reported routes are compared by silica and alumina precursor, SiO₂/Al₂O₃ ratio, pH, crystallisation temperature (90–180 °C) and time, achievable crystallinity, and characterisation by XRD, SEM, FTIR, BET, and TGA. Evidence indicates that biodegradable agents can direct crystalline zeolite frameworks under milder, less hazardous conditions, although attaining the high Si/Al ratios required for ZSM-5 remains challenging with these weaker templates. Coupling such agents with low-cost local feedstock—rice husk ash as a silica source and metakaolin as an alumina source—offers a sustainable, lower-cost pathway to ZSM-5 suited to Nigeria’s downstream petroleum sector and circular-economy goals. The review identifies gaps in reproducibility, template–framework interactions, and scale-up, and outlines directions for developing fully green, waste-derived zeolite catalysts.

Keywords ZSM-5 zeolite biodegradable structure-directing agents green synthesis rice husk ash metakaolin

Comparative Study of Thermal, Zeolite-Y Catalytic and Ni-Doped Zeolite-Y Catalytic Cracking of Gas Condensate

Jonathan Danladi Gaiya — Chemical Engineering, Ahmadu Bello University, Zaria

Shuaibu Musa — Chemical Engineering, Ahmadu Bello University, Zaria

Suleiman Shehu — Chemical Engineering, Ahmadu Bello University, Zaria

Mansur Suleiman — Chemical Engineering, Ahmadu Bello University, Zaria

Abdullahi, Nuraddeen Bakori — Chemical Engineering, Ahmadu Bello University, Zaria

Narcillina Nkechi Adegboro — Chemical Engineering, Ahmadu Bello University, Zaria

Muhammad Aminu Abubakar — Chemical Engineering, Ahmadu Bello University, Zaria

Aliyu Ibrahim — Chemical Engineering, Ahmadu Bello University, Zaria

Abdullahi Bukar — Chemical Engineering, Ahmadu Bello University, Zaria

Muazu Ibrahim — Chemical Engineering, Ahmadu Bello University, Zaria

Toyese Oyegoke — Chemical Engineering, Ahmadu Bello University, Zaria

Abdulazeez Yusuf Atta — Chemical Engineering, Ahmadu Bello University, Zaria

This study investigated the modification of Zeolite-Y and its application in the cracking of gas condensate using thermal, catalytic, and nickel-doped catalytic processes. Raw Zeolite-Y (ZY-1) was chemically pretreated (ZY-2) and subsequently modified with nickel to produce Ni-doped Zeolite-Y (ZY-3). The catalysts were characterized using Brunauer–Emmett–Teller (BET) analysis, X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FTIR), while the hydrocarbon products were evaluated by GC-MS/PIONA analysis. BET analysis showed progressive increases in surface area from 181.549 m²/g for ZY-1 to 245.368 and 278.956 m²/g for ZY-2 and ZY-3, respectively, accompanied by increases in total and micropore volumes. XRD confirmed preservation of the characteristic Zeolite-Y framework after modification, with additional reflections in ZY-3 consistent with crystalline NiO. FTIR further confirmed retention of the principal aluminosilicate framework vibrations following pretreatment and nickel incorporation. GC-MS/PIONA analysis revealed substantial changes in hydrocarbon-class distribution following cracking. The raw gas condensate (G-1) contained 47.47% paraffins and 30.49% aromatics, while thermal cracking (G-2) produced 46.10% paraffins and 32.10% aromatics. Catalytic cracking (G-3) increased the aromatic fraction to 40.90% while reducing paraffins to 38.40%. Ni-doped catalytic cracking (G-4) resulted in 39.48% aromatics, 39.98% paraffins, and a slight increase in olefins from 0.40% to 0.91% relative to G-3. Overall, the results demonstrate that pretreatment and nickel incorporation significantly modified the textural and structural properties of Zeolite-Y, while catalytic and Ni-doped catalytic cracking produced distinct changes in gas-condensate hydrocarbon composition.

Keywords Zeolite-Y Nickel-doped Zeolite-Y Gas condensate Catalytic cracking Thermal cracking

Density Functional Theory Investigation of Methane Steam Reforming on Ni(111) and Pd1–Cu(111) Single-Atom Alloy Surfaces

Abdulrauf Onimisi Ibrahim — Ahmadu Bello University

Density functional theory (DFT) calculations were performed to investigate the elementary reaction steps involved in methane steam reforming on Ni(111) and Pd1–Cu(111) single-atom alloy catalyst (SAAC) surfaces. The reaction pathway includes methane and water dissociation, oxidation of CH* by adsorbed oxygen to form CHO*, and subsequent dehydrogenation of CHO* to CO. The objective of this study is to evaluate the catalytic potential of the Pd1–Cu(111) SAAC as a carbon-tolerant alternative to conventional Ni catalysts while maintaining high reforming activity. The results show that methane activation on Pd1–Cu(111) proceeds with an activation barrier of 0.97 eV, which is 0.32 eV lower than that on Ni(111), indicating enhanced CH4 activation. In contrast, water dissociation is less favorable on Pd1–Cu(111), with an activation barrier 0.39 eV higher than that on Ni(111). Notably, the formation of surface carbon from CH* is kinetically inhibited on the Pd1–Cu(111) SAAC because of its substantially higher activation barrier, thereby suppressing coke formation. Overall, these findings demonstrate that the Pd1–Cu(111) single-atom alloy effectively promotes methane activation while minimizing carbon deposition, highlighting its promise as a highly active and coke-resistant catalyst for methane steam reforming.

Keywords Density functional theory methane steam reforming alloy catalyst

Determination of Low-Temperature Low-Pressure (LTLP) Filtration Properties of Drilling Mud Formulated from Arawa Bentonite Clay for Oil and Gas Drilling Application

Bala Usman — Ahmadu Bello University, Zaria

Bilal Sabiu — Ahmadu Bello University, Zaria

Hamza Abdulhamid — Ahmadu Bello University, Zaria

Muhammad Tukur — Cert, Ahmadu Bello University, Zaria

Abubakar Sadeeq Hussain — Ahmadu Bello University, Zaria

Kabiru Suleman — Ahmadu Bello University, Zaria

Filtration control is an essential activity during drilling because excessive fluid loss to permeable formation causes wellbore instability, acute drilling performance, differential pipe sticking and formation damage. In this study, Low-Temperature Low-Pressure (LTLP) Filtration Properties of Drilling Mud Formulated from Nigerian Arawa Bentonite Clay was investigated. Filtrate loss, spurt loss and leak-off coefficients for API base, API Standard, raw Arawa, Arawa base, Arawa standard and Arawa standard treated with sub-micron calcium carbonate formulation was evaluated using API low temperature filter press at 100 psi at room temperature. Filtrate volume was measured as a function of time up to 30 minutes while spurt loss (Vs) and leak-off coefficient (K) were determined by fitting the experimental data into Carter filtration model. The results have shown that API base, API Standard, raw Arawa, Arawa base, Arawa standard formulation and Arawa standard formulation treated with sub-micron calcium carbonate formulation have LTLP fluid loss of 8ml, 7.6ml, 14ml, 12ml, 8.6ml, and 7.8ml respectively making the fluid loss within API standard requirement of ≤15ml. The formulations have shown spurt loss of 6.7423x10-16ml, 4.86 x10-16ml, 9.9449 x10-16ml, 1.0337 x10-16ml, 3.7923 x10-17ml and 5.7679 x10-17ml respectively, and leak-off coefficient of 1.46ml.min-1/2, 1.37ml.min-1/2, 2.49ml.min-1/2, 2.12ml.min-1/2, 1.49ml.min-1/2 and 1.34ml.min-1/2 respectively. The model performance statistics have shown good correlation between Experimental and model parameters with average R-square, adjusted R-square and Sum of Square Error (SSE) of 0.97697, 0.97121and 0.5 respectively. The study demonstrates the potential of beneficiated and standardized Nigerian Arawa bentonite clay as locally sourced constituents of drilling mud for Oil and Gas drilling application.

Keywords Drilling mud LTLP filtration Arawa bentonite soda activation calcium carbonate sub-micron Carter filtration model API base API standard spurt loss (Vs) leak-off coefficient R-square.

Development and Microstructural Characterization of Al-Si-Mg / Giro Clay Nanoparticle Composites Fabricated via Stir Casting for Marine Applications

Youshau Najee Abdusalam — Ahamadu Bello University, Zaria

Kasim Auwal — Met And Mat Eng Department, Ahmadu Bello University, Zaria, Nigeria

Abdulwahab Malik — Met And Mat Eng Department, Ahmadu Bello University, Zaria, Nigeria

Gaminana Jimoh O. — Met And Mat Eng Department, Ahmadu Bello University, Zaria, Nigeria

Abdullahi Ibrahim — Met And Mat Eng Department, Ahmadu Bello University, Zaria, Nigeria

Adegbite Dauda A. — Metallurgical Engineering Department, Iot, Kwara State Polytechnic, Ilorin, Nigeria

The increasing demand for lightweight, corrosion-resistant materials in marine engineering necessitates the development of cost-effective aluminum matrix composites (AMCs) using locally sourced reinforcements. This study focuses on the development and characterization of Al-Si-Mg alloy reinforced with Giro clay nanoparticles (GCNP) for potential marine structural applications.
The Giro clay was beneficiated and processed into nanoparticles, followed by a comprehensive chemical and phase characterization using X-Ray Fluorescence (XRF) and X-Ray Diffraction (XRD). The analyses revealed the presence of protective ceramic phases, notably Al₂O₃, SiO₂, CaO, and Fe₂O₃, confirming its viability as a reinforcing agent. The composites were developed via the stir casting route, with reinforcement concentrations systematically varied from 0 to 10 wt.% at 2 wt.% intervals. The as-cast alloy and developed composites were rigorously characterized using Scanning Electron Microscopy coupled with Energy-Dispersive X-ray Spectroscopy (SEM/EDS) to evaluate the dispersion of nanoparticles, grain refinement, and elemental distribution within the aluminum matrix.
Microstructural analysis confirmed a relatively uniform dispersion of the Giro clay nanoparticles at lower weight fractions, with evidence of grain boundary pinning and reduced dendrite arm spacing. While the overarching goal includes corrosion resistance, the primary novelty of this work lies in the successful integration of this locally abundant Nigerian clay into a structural alloy. The stir-casting parameters were optimized to minimize porosity and achieve acceptable wettability between the ceramic phases and the Al-Si-Mg matrix. The fabricated composites demonstrated structural integrity, with the 4 wt.% reinforcement formulations exhibiting the most refined microstructure and optimal phase distribution.
This study successfully establishes a processing-structure-property linkage for Giro clay-reinforced AMCs, demonstrating that locally sourced nanoparticles can be effectively utilized to develop advanced engineering materials suitable for harsh environments, positioning this research as a significant step toward self-reliance in marine material technology.

Keywords Al-Si-Mg Alloy Giro Clay Nanoparticles Stir Casting Microstructural Characterization XRD/SEM-EDS Marine Materials

Effect of Double Pressing and Double Sintering on the Mechanical and Tribological Properties of Aluminium Matrix Reinforced Rice Husk Ash Composites

Abdulrahman Adeiza Musa — Department Of Metallurgical And Materials Engineering, Ahmadu Bello University Zaria

Kamilu Adeyemi Bello — Department Of Metallurgical And Materials Engineering, Ahmadu Bello University Zaria

Agbo E. Oloture — Ahmadu Bello University Zaria

Mohd A. Maleque — Department Of Manufacturing And Materials Engineering, International Islamic University Malaysia, Kuala Lumpur, Malaysia

Gaminana Jimoh O. — Department Of Metallurgical And Materials Engineering, Ahmadu Bello University, Zaria

Rayyan Mamuda Dodo — Department Of Metallurgical And Materials Engineering, Ahmadu Bello University, Zaria

Hayatu M. Abdullahi — Department Of Metallurgical Engineering. Kaduna Polytechnic, Kaduna. Nigeria

Abdullahi Umma — Department Of Mechanical Engineering, Bayero University, Kano, Nigeria

This study investigates the effect of double pressing and double sintering (DPDS) on the mechanical and tribological properties of aluminum matrix composites reinforced with rice husk ash (RHA). Aluminum–RHA composites containing 0–15 wt.% RHA were fabricated using powder metallurgy through three processing routes: single pressing–single sintering (SP–SS), single pressing–high-pressure sintering (SP–HPS), and double pressing–double sintering (DPDS). Hardness, wear rate, and coefficient of friction (COF) were evaluated, with representative values obtained under stable sliding conditions used to establish physically meaningful correlations. The DPDS route produced higher hardness values for both pure aluminum (69.9 HV) and the 5 wt.% RHA composite (78.0 HV), with the corresponding lowest specific wear rates of (8.33 × 10⁻⁷ mm³/N·m) and reduced coefficients of friction (COF) of 0.195 and 0.203, respectively. A clear inverse relationship between hardness and specific wear rate was observed for pure aluminum and the 5 wt.% RHA composites, consistent with classical tribological principles. However, composites containing 10–15 wt.% RHA exhibited increased wear and friction despite their relatively higher hardness, which was attributed to particle agglomeration, weak interfacial bonding, and abrasive wear associated with the silica-rich RHA particles. These findings demonstrate that DPDS is an effective processing route for improving the tribological performance of aluminum–RHA composites, with 5 wt.% RHA providing the best combination of hardness, wear resistance, and coefficient of friction under the investigated conditions. The use of locally sourced RHA in this study promotes agricultural waste valorization and sustainable materials development, supporting the global goal of advancing environmentally responsible engineering solutions.

EFFECT OF HEAT TREATMENT AND QUENCHING MEDIA ON THE MECHANICAL TRIBOLOGICAL THERMAL AND MICROSTRUCTURAL BEHAVIOUR OF A6082-SNSA/MWCNT HYBRID COMPOSITES

Abdullahi Mohammed

Malachy Sumaila — Department Of Mechanical Engineering, Faculty Of Engineering, Ahmadu Bello University Zaria, Nigeria

Muhammad Dauda — Department Of Mechanical Engineering, Faculty Of Engineering, Ahmadu Bello University Zaria, Nigeria

Laminu Shattima Kuburi — Department Of Mechanical Engineering, Faculty Of Engineering, Ahmadu Bello University Zaria, Nigeria

The effect of heat treatment and different quenching media on the mechanical, tribological, thermal and microstructural behaviour of A6082–SNSA/MWCNT hybrid composites was studied. The fabricated composites were subjected to heat treatment and quenched in tap water (TW), ice block (IB), and SAE40 engine oil (SEO), and their properties were compared with untreated hybrid composites and the base matrix alloy. The result of the mechanical properties revealed that all heat-treated samples exhibited significant improvements in hardness, compressive strength, and impact strength relative to the untreated composite. The IB quenched sample recorded the highest hardness of 155.33 Hv, representing 15% increment, while the TW quenched sample exhibited superior compressive and impact strengths of 1567.1 MPa representing 64.30% and 3.0J respectively. Tribological analysis showed that the SEO quenched composite possessed the lowest coefficient of friction of 0.166, which represents 16.27% improvement, whereas the TW quenched composite demonstrated the most favourable wear performance among the treated samples. Optical microstructural analysis revealed that rapid quenching (IB) produced the finest and most compact dendritic network, while oil quenching resulted in coarse, elongated dendrites with increased segregation and micro-voids. Scanning electron microscope (SEM) analysis of the worn surfaces confirmed dominance of abrasive and delamination wear mechanisms, with reduced surface damage observed in heat-treated samples. The results of the study have demonstrated that heat treatment significantly enhances the performance of A6082–SNSA/MWCNT hybrid composites, with quenching medium playing a critical role in their properties and microstructure of the hybrid composites.

Keywords A6082 aluminium alloy Hybrid metal matrix composites Heat treatment Quenching media Microstructure

EVALUATION OF DIFFERENT COMPUTATIONAL STRATEGIES FOR THE FORMULATION OF IONIC LIQUIDS FOR SUGAR SOLUBILITY APPLICATION

Ibrahim Ibrahim — Ahmadu Bello University Zaria

Suleiman Shuwa — Department Of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria

Oyegoke Toyese — Department Of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria

Abdulkareem Abubakar — Department Of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria

Suleiman Yunusa — Department Of Chemical Engineering, Nasarawa State University, Keffi, Nigeria

Alewo Opuada Ameh — Department Of Chemical Engineering, Federal University, Wukari, Nigeria

Abstract
This study introduces a computational screening strategy for ionic liquids (ILs) aimed at enhancing the separation of fructose–glucose mixtures, a critical step in Bio refinery processes. Different modelling strategy for the IL candidates were Evaluated. Six computational screening methods (M1–M6) were Considered. M1, (Density functional theory from molecular mechanics first principle with geometry optimization, SCF tolerance equal to 5) achieved the highest accuracy (99.9%), its computational cost was excessive. Method M3, combining PM3 equilibrium conformer with SCF tolerance = 9, plus DFT energy calculation (SCF tolerance = 5), delivered comparable accuracy (99%) with moderate computational time. This balance established M3 as the optimal Strategy for IL screening. Using M3, ILs were systematically assessed for sugar separation potential, highlighting promising candidates for glucose-fructose mixture isolation. The study demonstrates how hybrid computational workflows can accelerate IL discovery while maintaining predictive reliability, offering a scalable pathway for Sugar application.

Keywords computational strategy ionic liquids Sugar.

Geospatial Assessment of Soil Textural Classes and the Implications on Achieving SDG 2 in Northwest Nigeria

Halimat Suraj Garuba — Ahmadu Bello University, Zaria

Mujahid, M.m — Ahmadu Bello University, Zaria

Mukhtar, M.k — Fudma

This study presents a geospatial analysis of soil textural classes for Kaduna, Kano and Katsina States, all located in the North-western region of Nigerian. The soil classification maps were digitized from the FAO Digital Soil Map of the World (DSMW) using ArcGIS 10.3.1. The results revealed that sandy-Loam is the most dominant soil class in Kano and Katsina states. Kaduna State revealed a greater variability in soil classes, with larger areas of the state dominated by Loam, then Sandy Clay Loam and Sandy Loam. The results of soil textural classes correlates with the inherent soil properties associated with the Sudan Savanna agro-ecological zone. The study provides a spatial framework for achieving precision agriculture technology required to achieve SDG 2 (Zero Hunger). The study recommends a ground- truthing physical-chemical analysis of soil samples across the States.

Keywords ArcGIS FAO Northwest SDG2 Soil

Investigation into the Use of Locally Available Materials for the Production of Investment Casting Mould

Nura Lawal — Department Of Mechanical Engineering, Bayero University Kano Nigeria

Prof. Mahadi Makoyo — Department Of Mechanical Engineering, Bayero University Kano Nigeria

Prof. Adamu Umar Alhaji — Department Of Mechanical Engineering,bayero University Kano Nigeria

Yakubu Shuaibu Ochetengwu — Department Of Mechanical Engineering, Nda Kaduna.

Abstract. Investment casting produces high-quality, dimensionally accurate parts with complex geometries that forging and machining cannot easily achieve, but imported refractories and binders make the process expensive to adopt. This study investigated locally available moulding plaster, cassava flakes, kaolin, Portland cement, and fine sand as substitutes, using beeswax as the pattern material. Particle size, viscosity, flexural strength, and refractoriness were determined. Viscosity reached 710 mPa·s for moulding plaster, 650 mPa·s for cassava flakes, and 613 mPa·s for kaolin, while flexural strength reached 105.60 MPa for moulding plaster, 80.00 MPa for Portland cement, and 52.13 MPa for kaolin. Six trial compositions were evaluated and an optimum blend containing 82% moulding plaster, 5% cassava flakes, 5% cement, 4% kaolin, and 4% fine sand was selected. The fired mould achieved flexural strengths of 159.25, 139.00, and 154.75 MPa for three samples, with an average permeability of 92 AFS. A brass jewellery piece was successfully cast in the finished mould. The findings demonstrate the feasibility of combining locally available materials into a functional investment casting system without imported refractories.

Keywords investment casting locally sourced refractories: binders ceramic shell mould beeswax brass casting

Mechanical, Optical and Engineering Assessment of Polypropylene/Fiberglass Composites for Translucent LPG Cylinder Applications

Usman Sani — Kaduna Polytechnic

Fatima Mohammed — Ahmadu Bello University Zaria

Simon N.n — Institute Of Leather Research, Zaria, Kaduna State, Nigeria

The increasing demand for safer, lightweight, and corrosion-resistant liquefied petroleum gas (LPG) cylinders has created the need for alternative materials that overcome the limitations of conventional steel cylinders. This study presents the conceptual design and material evaluation of a translucent composite LPG cylinder based on PP/FG composites. The conceptual design integrates a lightweight polymer composite shell capable of withstanding service loads while providing sufficient light transmittance to enable direct visual monitoring of LPG level without auxiliary gauges. Five PP/FG formulations (40/60, 45/55, 50/50, 55/45, and 60/40 wt%) were developed through melt compounding and compression moulding to identify the optimum material for the proposed cylinder. Mechanical performance was assessed through tensile, flexural, impact, and hardness testing, while optical suitability was evaluated using indoor and outdoor light transmittance measurements. The results showed that composite composition significantly influenced both structural and optical properties. The 55/45 PP/FG formulation exhibited the highest tensile strength (33.17 MPa) and the greatest light transmittance (9.50% indoors and 24.30% outdoors), demonstrating the best balance between strength and translucency. A normalized performance evaluation further confirmed this formulation as the optimum material for the conceptual cylinder design. The proposed composite cylinder offers significant advantages over conventional steel cylinders, including reduced weight, improved corrosion resistance, and the ability to visually monitor LPG content, thereby improving user convenience and operational safety. The study demonstrates the feasibility of integrating material selection and conceptual design in the development of next-generation translucent composite LPG cylinders.

Keywords Polypropylene fiberglass composite Conceptual design LPG cylinder Mechanical properties Light transmittance

Performance Evaluation of Lateritic Adobe Bricks Stabilized with Granite Powder: Strength, Durability, and Thermal Resilience

Yunusa Tsoho Abdullahi — Aliko Dangote University Of Science And Technology Wudil

Nasiru Zakari Muhammad — Aliko Dangote University Of Science And Technology Wudil

Ado Ma'aruf — Aliko Dangote University Of Science And Technology Wudil

Mujitafa Sariyyu — Aliko Dangote University Of Science And Technology Wudil

Zaharaddeeen Baffa Baba — Aliko Dangote University Of Science And Technology Wudil

Abstract
Traditional adobe bricks offer excellent thermal insulation and affordability but suffer from low compressive strength, high water absorption, and poor durability. Conventional stabilizers like cement and lime carry a massive environmental footprint and are economically unviable for low-income housing. This study investigates the potential of Granite Powder (GP)—a quarrying by-product—as a sustainable, zero-cement stabilizer for lateritic adobe bricks. Ten mix formulations were developed, including an unstabilized control and six GP-only variants (5%, 10%, 15%, 20%, 25%, and 30% by mass of laterite). Specimens were subjected to compressive strength testing, 24-hour water immersion, modified capillary wetting assessment, thermal conditioning (40°C, 60°C, and 100°C), and porosity evaluation. Results indicate that a 10% GP inclusion yielded the highest compressive strength (3.34 N/mm² at 28 days), a 30% increase over the control, surpassing the 3.0 N/mm² benchmark for non-seismic earthen construction (I

Keywords Granite powder Adobe bricks Compressive strength Water absorption Sustainable construction Circular economy.

Production of Silica from Agricultural Wastes for Application in FCC/RFCC Catalyst Development: A Mini Review

Usman Sani — Kaduna Polytechnic

Daniel Adanenche — Research And Development Centre, Dangote Petroleum Refinery And Petrochemicals, Fze, Union Marble House, Ikoyi, Lagos, Nigeria.

Mustapha Yusuf — Department Of Chemical Engineering, Ahmadu Bello University, Zaria, Nigeria

A. Y. Atta

B. J. El-yakubu

Fluid catalytic cracking (FCC) and its residue variant (RFCC) are central to converting heavy petroleum fractions into gasoline and light olefins, and their catalysts depend on silica as both a binder and a precursor for the zeolite-Y active component and the active matrix. Conventional silica sources—tetraethyl and tetramethyl orthosilicate, sodium silicate, and fumed silica—are pure but costly, toxic, and energy-intensive, motivating a search for green alternatives. This mini-review examines the production of silica from agricultural wastes and its application in FCC/RFCC catalyst development. Rice husk, rice straw, sugarcane bagasse, and corn cob yield amorphous silica of high purity (commonly 90–98%) after acid leaching, controlled calcination, and alkaline dissolution to sodium silicate. In Nigeria alone, these residues are generated at an estimated 10.8 million tonnes per year, much of it burnt or left to create a nuisance, so their valorisation is at once an environmental and an economic opportunity. The review considers how agricultural-waste silica can supply the sodium-free silica binder and the silica source for seeded zeolite-Y synthesis, with metakaolin as the alumina source, and how it must satisfy the low-sodium, high-purity, reactivity, and attrition-resistance requirements specific to cracking catalysts. It concludes that agricultural-waste silica is a viable, sustainable precursor for FCC/RFCC catalysts, and identifies impurity control, feedstock variability, catalyst-grade specification, and scale-up as the principal challenges to industrial adoption.

Keywords Agricultural waste silica Rice husk ashk FCC/RFCC catalyst Zeolite-Y Green materials

Sugarcane Bagasse Ash as a Sustainable Silica Precursor for Zeolite Synthesis: A Review of Extraction Routes

Gabriel Christopher — Ahmadu Bello University Zaria

Abdulazeez Yusuf Atta — Ahmadu Bello University Zaria

Baba Jibril El-yakubu — Ahmadu Bello University Zaria

Ajayi Olusegun Ayoola — Ahmadu Bello University Zaria

Mustapha Yusuf — Ahmadu Bello University Zaria

Abstract
Zeolite synthesis requires reactive silica sources, which are conventionally supplied by costly and energy-intensive reagents such as tetraethyl orthosilicate and sodium silicate. Sugarcane bagasse ash (SCBA), an abundant sugar-industry residue, provides a low-cost, renewable alternative due to its high silica content. In Nigeria, the three major sugar industry generates an estimate of 1 million metric tonnes of bagasse annually, highlighting the potential for converting this underutilised residue into a valuable feedstock. This review compares principal silica extraction routes from SCBA and evaluates their suitability for ZSM-5 synthesis from SCBA and metakaolin. The conventional route involves acid leaching, calcination near 600 °C, alkaline dissolution in sodium hydroxide, and acid precipitation. Although this route produces amorphous, high-surface-area silica and high recovery but high energy and reagent consumption. Calcination-free acid–alkali extraction offers a more sustainable alternative by directly dissolving SCBA in sodium hydroxide and precipitating silica using hydrochloric acid, producing silica with purity of approximately 98% while reducing energy demand. Characterisation using XRD, FTIR, BET, and electron microscopy provides information on phase composition, functional groups, surface area, and morphology. The extraction route strongly influences silica purity, recovery, reactivity, and sustainability. Calcination-free approaches are particularly promising for green ZSM-5 synthesis, although optimisation of yield, impurity removal, reagent consumption, and scale-up remains necessary for industrial application.

Keywords sugarcane bagasse ash silica extraction ZSM-5 zeolite green synthesis waste valorisation..

An Edge AI-Driven Cyber-Physical Framework for Green Network Optimization and Resilient Infrastructure in Emerging Economies

Sani Muhammed Hassan — Federal University Of Techology Babura

Muhammad Ahmad Abdulkadir — Federal University Of Technology Babura

In emerging economies, the deployment of next-generation digital infrastructure faces severe operational hurdles, including volatile power grids, limited bandwidth, and high energy costs. Traditional cloud-centric architectures exacerbate these challenges by requiring continuous data transmission, which strains local telecommunications networks and increases carbon footprints. This paper proposes a decentralized, Edge AI-driven cyber-physical framework designed to optimize green network operations and enhance infrastructural resilience under severe resource constraints. By deploying lightweight machine learning algorithms directly at the network edge, the framework enables real-time, localized telemetry processing and anomaly detection without relying on continuous cloud connectivity.
The cyber-physical system (CPS) architecture integrates an intelligent power-and-data routing layer that dynamically balances computational workloads based on localized energy availability and network health. To achieve green network optimization, we introduce a predictive power-saving algorithm that transitions edge nodes into low-power states during periods of low activity, significantly reducing the aggregate carbon intensity of the IT infrastructure. Simulations modeled on regional infrastructure constraints demonstrate that the proposed framework reduces data transmission volume to centralized clouds by up to 65%, cuts edge-node energy consumption by 30%, and maintains system uptime during simulated localized power outages. Ultimately, this research provides a scalable, eco-friendly blueprint for accelerating digital transformation and building resilient, sustainable IT systems in developing regions.

Keywords Edge Artificial Intelligence Cyber-Physical Systems (CPS) Green IT Network Optimization Infrastructure Resilience Emerging Economies Digital Transformation Sustainable Computing Internet of Things (IoT) Telemetry.

ARTIFICIAL INTELLIGENCE BASED SECURITY FRAMEWORK FOR WIRELESS INTERNET OF THINGS COMMUNICATION FOR DEVICES WITH HETEROGENEOUS ARCHITECTURE

Nicodemus Awobi — University Of Abuja

This work titled Artificial Intelligence Based Security Framework For Wireless Internet of Things Communication was carried out to actualise the fundamental problem encountered by different models of secirity of IoT as a result of different architectural background . This study adopts a descriptive and analytical research design aimed at developing and evaluating an AI-driven security framework for IoT networks. The approach combines machine learning (ML), deep learning (DL), and explainable AI (XAI) techniques to identify, predict, and mitigate cybersecurity threats in heterogeneous IoT environments. A descriptive design allows for detailed observation of IoT traffic patterns, attack vectors, and system behavior under controlled and real-world conditions. Furthermore,The population consists of all network traffic events and sensor readings generated within the IoT environment, including benign and attack traffic. For experimental evaluation, a representative sample of these data points is collected from simulated smart building testbeds, IoT traffic datasets (e.g., NSL-KDD), and real-time IoT sensor streams. Stratified sampling ensures proportional representation of each attack type, including Denial-of-Service (DoS), User-to-Root (U2R), Remote-to-Local (R2L), probe, and malware attacks, thereby enhancing model generalizability. this study implements robust data balancing techniques to ensure equitable representation of all attack subcategories within the training datasets. Imbalanced datasets often lead to biased or inaccurate predictions, which can compromise security in operational environments. By applying sophisticated balancing strategies, the framework enhances the model’s ability to generalize across varied attack scenarios and real-world traffic conditions. This strengthens the framework’s overall reliability and reduces the likelihood of overlooking rare but critical cyber threats.

Keywords ARTIFICIAL INTELLIGENCE SECURITYFRAMEWORK WIRELESS INTERNET COMMUNICATION DEVICES HETEROGENEOUS ARCHITECTURE

COMPUTATIONAL INVESTIGATION OF ACTIVE PALM OIL COMPONENTS AS ECO-FRIENDLY CORROSION INHIBITORS FOR COPPER METALS

Usman Sani — Kaduna Polytechnic

Abdulazeez Abdulateefa — Ahmadu Bello University Zaria

Amaram Jonah Adams — Ahmadu Bello University Zaria

Oyegoke Toyese — Ahmadu Bello University Zaria

This study investigates the corrosion inhibition potential of selected palm oil constituents using Spatan24 by PM6 and B3LYP Methods in a gaseous medium and a convergence criteria of 1E-5 a.u. with SCFCYCLE of 99000. The constituents considered includes: myristic, linoleic, stearic, oleic, lauric, and palmitic acids on copper exposed to corrosive compound typically found in industrial environments. Quantum chemical parameters, including total electronic energy (E), highest occupied molecular orbital energy (E-HOMO), lowest unoccupied molecular orbital energy (E-LUMO), energy band gap (Egap), and interaction energy gaps (IEG1 and IEG2), were evaluated to understand the reactivity and inhibition efficiency of these compounds and were compared with that of styrene an active corrosion protection component of paint. Among the analyzed compounds, Linoleic acid demonstrates the highest inhibition capability for copper corrosion protection caused by aggressive species like H₂SO₄, HCl, HNO₃, and NaCl. Its superior electronic properties: high HOMO (9.66 eV), low Egap (9.53eV), low IEG (6.41eV) values) and molecular structure make it an excellent candidate for corrosion protection applications. These findings suggest that stearic acid could serve as an efficient, eco-friendly inhibitor in copper corrosion prevention.

Keywords copper corrosion palm oil inhibitors quantum chemical analysis HOMO-LUMO Egap stearic acid corrosion protection

DEVELOPMENT OF A HYBRID SUPPORT VECTOR MACHINE AND BAT OPTIMIZATION ALGORITHM FOR ENHANCED SPECTRUM SENSING IN TELEVISION WHITE SPACE NETWORKS

Yahaya Hamisu Abubakar — University Of Porthacourt

Mathew Ehikhamenle — Center For Information And Telecommunication Engineering (cite), University Of Portharcourt

This paper presents the findings of a research on an artificial intelligence-based hybrid Support Vector Machine–Bat Optimization Algorithm (SVM-BOA) model developed for spectrum sensing in the Ultra High Frequency (UHF) television band (470 – 694 MHz). The main objective is to enhance detection accuracy, probability of detection, probability of false alarm, and computational efficiency for efficient spectrum utilization. Experimental spectrum measurements were conducted across Kano, Kaduna, and the Federal Capital Territory (FCT), Abuja, Nigeria, to assess the level of spectrum occupancy and identify available Television White Space (TVWS) channels. Relevant signal features, including received signal power level, noise power level, and frequency, were extracted from the field data collected and used to train and test the proposed model. The model was developed and implemented in MATLAB computing environment. The new model was validated using test data for classification of channel status as either free or occupied. The developed model achieved a detection accuracy of 97.67% at a threshold of −99.5dB, based on metric from confusion matrix, outperforming baseline SVM (78.57%) and other benchmark optimization-based SVM models, including Grid Search SVM (92.86%), Random Search SVM (89.29%), Genetic Algorithm SVM (92.86%), and Particle Swarm Optimization SVM (92.78%). It also attained a probability of detection (Pd) of 1.00 (100%) and a probability of false alarm (Pfa) of 0.1053 (10.53%), which satisfies the sensing performance requirements of the Institute of Electrical and Electronics (IEEE 802.22) standards under low-signal conditions. These findings suggest that the hybrid SVM-BOA approach will offer superior classification accuracy and computational efficiency relative to conventional techniques and comparable hybrid models, signifying a strong potential for the improvement of spectrum utilization in next-generation cognitive radio networks.

Keywords Cognitive Radio Television White Spaces (TVWS) Spectrum measurement campaign Spectrum Sensing Machine Learning Support Vector Machine (SVM) Bat Algorithm Meta-heuristic Optimization.

Factors Influencing the Adoption of Mixed Reality Technology for Construction Projects Cost Estimation

Raphael Olarewaju — Federal University Of Technology Akure

Olubunmi Comfort Ade-ojo — Federal University Of Technology Akure (futa) / Department Of Quantity Surveying

Cost estimation issues including budget overruns, delays in project delivery, and loss of stakeholder confidence remain as persistent challenges in the Nigerian construction Industry. By integrating Augmented Reality (AR) and Virtual Reality (VR) to visualize design and cost data in an interactive and real-time manner, Mixed Reality (MR) technology promises to enhance estimation precision, teamwork, and decision-making efficiency. Despite increasing interest in MR adoption in the construction industry, it is still not well explored in the Nigerian context, especially among Quantity Surveyors (QSs) for construction cost estimation. This study has investigated the factors influencing the adoption of MR technology for construction cost estimation among QSs in Lagos State, Nigeria. Five (5) latent constructs namely, Organizational Factors (ORGF), Infrastructural Factors (INFF), Training-Related Factors (TRF), Financial Viability Factors (FVF), and Institutional Factors (INSTF) were measured using a structured questionnaire via census sampling, which got 87.85% response rate. Data from 94 respondents were analyzed using Confirmatory Factor Analysis (CFA) in JASP software. The CFA model showed good model fit (CFI = 0.973, TLI = 0.968, RMSEA = 0.054, and SRMR = 0.053), and the five constructs achieved convergent validity (AVE ≥ 0.70) and high internal consistency (α and ω ≥ 0.89). The results validate that organizational support, digital infrastructure, professional training, financial readiness, and institutional frameworks are important influencing factors of MR technology adoption in construction cost estimation. The findings give practical guidance to construction companies, government authorities, and professional organizations for promoting the uptake of MR in the construction industry in Nigeria.

Keywords Mixed Reality Construction Cost Estimation Technology Adoption Quantity Surveyors

Intelligent Energy Management in Agriculture: A Systematic Review of Internet of Thing, Renewable Integration, and Artificial Intelligence Techniques

Vandi Jusu — Federal University Of Technology Minna

Eugene Okenna Agbachi — Federal University Of Technology Minna

Jibril Abdullahi Bala — Federal University Of Technology Minna

Drawing on an analysis of 85 studies in the period 2020-2026, this review examines how smart technologies are utilized for energy management in agriculture. This review uncovers current trends and future trajectories across six themes: farm energy monitoring made possible by IoT; the incorporation of renewables into agricultural operations; forecasting of energy needs for the storage and processing of crops; policy frameworks for agro-energy; the use of AI to optimise heavy-duty farming equipment; and blockchain for peer-to-peer energy trading on rural grids. Among the key findings is the capacity of AI to transform on-farm energy consumption through demand-response in livestock and irrigation facilities and a better integration of decentralised renewables in microgrids. At the same time, the study highlights several shortcomings, particularly regarding system scalability for farms of different sizes, the real-time demands of variable weather and crop cycles, and the computational limits encountered off-grid. A four-step methodology has been employed to bridge the divide between theoretical propositions and practical implementation challenges, thus providing a road map to a smart EMS that is both resilient and economical for agri-food value chains. In so doing the research puts forward a comprehensive framework for agricultural engineers, researchers and energy policymakers to build more sustainable farm energy systems and surmount the obstacles to field-level deployment that are peculiar to the rural environment.

Keywords Demand-Side Management Smart Farming Renewable Energy Artificial Intelligence Internet of Things Energy Forecasting Agricultural Electrification

Measurement of Liquid Film Height in Gas-Liquid Two-Phase Flows Using Twin-Wire Conductance Probes

Mohammed Abdullahi — Nuhu Bamalli Polytechnic Zaria

Accurate measurement of liquid film thickness is important in process equipment because it supports heat- and mass-transfer calculations. In gas-liquid two-phase flow, film thickness is also required for estimating liquid film holdup. Twin-wire conductance probes have been shown to provide reliable measurements of liquid film height in air-water two-phase flows. In this work, probes were fabricated from 0.5 mm platinum wire of 99.9% purity in the student workshop at Imperial College London using standard machining procedures. The probes were mounted on a 32 mm pipe to measure liquid film height in air-water stratified and slug flows. The resulting measurements were accurate, instantaneous, and suitable for tracking changes in liquid film thickness.

Keywords Liquid film holdup twin-wire conductance probes liquid film thickness

Student Verification Assistant: A Low-Cost Multimodal Biometric System for Secure Examination Identity Authentication

Zainab Mukhtar Abubakar — Ahmadu Bello University, Zaria

Abdulfatai Dare Adekale — Ahmadu Bello University, Zaria

Risikat Folashade Adebiyi — Ahmadu Bello University, Zaria

Abubakar Umar — Ahmadu Bello University, Zaria

Anas Zakari — Ahmadu Bello University, Zaria

Habeeb Bello-salau — Ahmadu Bello University, Zaria

Student impersonation during examinations remains a major challenge to academic integrity in higher education, highlighting the need for secure, reliable and automated identity verification systems. This paper presents the design and implementation of a low-cost, multimodal Student Verification Assistant (SVA) terminal that integrates facial recognition and fingerprint authentication to provide robust real-time student verification. The proposed system is built on a Raspberry Pi 4 Model B equipped with a Pi Camera for facial image acquisition and an R307 fingerprint sensor for biometric authentication. Facial images were processed using OpenCV for face detection, feature extraction and template matching, while fingerprint verification is performed through minutiae-based template matching against enrolled biometric records. A 2.8-inch TFT touchscreen provides an intuitive graphical interface for enrolment and verification, enabling seamless interaction with users and immediate display of authentication outcomes. Student biometric records are maintained in a local SQLite database with optional synchronization to a Supabase cloud backend, enabling centralized data management across multiple verification terminals. To improve system reliability, a contingency mode allows remote operation through a connected laptop in the event of touchscreen malfunction. Experimental evaluation on a prototype implementation involving enrolled students demonstrates verification accuracies of 94% for facial recognition and 96% for fingerprint authentication, with an average end-to-end verification time of 3.8 seconds per student. The multimodal authentication framework significantly improves verification reliability compared with single-biometric approaches while maintaining low computational overhead suitable for edge deployment. Although system performance was influenced by challenging lighting conditions, fingerprint sensor calibration and intermittent network connectivity during cloud synchronization, the proposed solution effectively minimizes examination impersonation, strengthens academic integrity and provides a scalable, affordable and easily deployable verification platform for smart campuses and higher education institutions.

Keywords Multimodal Biometrics Student Verification Facial Recognition Fingerprint Authentication Examination Security.

Application of Artificial Intelligence in Transportation Safety and Environmental Administration: A Systematic Review

Ahmad Abubakar — Federal University Of Transportation, Daura

Shehu Mohammed Yusuf — Department Of Computer Engineering, Ahmadu Bello University Zaria

Transportation systems are critical to economic development and societal mobility, yet they continue to impose substantial safety and environmental burdens, including more than 1.19 million annual road traffic fatalities and approximately one-quarter of global energy-related CO₂ emissions. Although Artificial Intelligence (AI) has emerged as a promising tool for addressing these challenges, existing reviews predominantly focus on individual transport modes or isolated applications, resulting in limited understanding of AI’s cross-modal role in transportation safety and environmental administration. This systematic review synthesises recent advances in AI and Machine Learning (ML) applications across road, rail, maritime, and air transportation. Following PRISMA 2020 guidelines, 120 studies published between 2018 and 2025 were identified from Scopus, Web of Science, IEEE Xplore, and TRID databases and analysed through qualitative synthesis. The reviewed studies demonstrate the effectiveness of AI techniques, including machine learning, deep learning, computer vision, reinforcement learning, graph neural networks, and transformer-based models, in accident prediction, risk assessment, incident detection, predictive maintenance, emission reduction, fuel optimisation, air-quality forecasting, and environmental monitoring. Reported studies showed improvements ranging from 15–30% in accident prediction performance, incident detection latency below 2 seconds, fuel-consumption reductions of 10–20%, and CO₂-emission reductions of 8–15%. Despite these advances, significant challenges remain regarding data interoperability, model explainability, cybersecurity, scalability, and real-world deployment. This review further identifies critical research gaps in multimodal integration, standardised benchmarking, governance frameworks, and the joint optimisation of safety and environmental objectives. By providing a comprehensive cross-modal synthesis and future research roadmap, the study establishes a foundational framework for advancing AI-enabled transportation safety and environmental administration toward safer, more sustainable, and intelligent mobility systems.

Keywords Artificial intelligence transportation safety environmental administration intelligent transportation systems sustainability multimodal transportation

ASSESSING THE IMPACT OF CLIMATE CHANGE ON GROUNDWATER RECHARGE POTENTIAL IN PALLADAN, ZARIA, KADUNA STATE, NIGERIA.

Samuel Adebamidele Morohunkola — Ahmadu Bello University

Aliyu Adamu Dandajeh — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria.

Nura Idris Abdullahi — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria.

Shamsuddeen Jumande Mohammad — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria.

Sani Yakubu Khalifa — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria

Bashir Tanimu — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria

Groundwater constitutes the primary source of potable water for communities in the Nigerian Basement Complex region, yet its sustainability is increasingly threatened by climate change-induced rainfall variability and anthropogenic land degradation. This study assessed groundwater recharge potential in Palladan Zaria, Kaduna State, Nigeria, using a GIS-based Multi-Criteria Decision Analysis (MCDA) and Weighted Overlay Analysis (WOA) framework integrated with the Analytical Hierarchy Process (AHP) for criterion weight derivation. Seven thematic criteria — rainfall (CHIRPS v2.0, 1981-2024), soil type (FAO Nigeria dataset), slope, geology (SRTM 30m DEM), lineament density (terrain roughness proxy), drainage density (GRASS r.watershed), and land use/land cover (Landsat 8/9 OLI NDVI, November 2022) were acquired, pre-processed in QGIS, reclassified to a 1-5 ordinal scale, and combined using AHP-derived weights. The AHP pairwise comparison yielded a Consistency Ratio (CR) = 0.025 (< 0.10 threshold), confirming statistical reliability. Key results included mean annual rainfall of 966.21 mm/year, mean slope of 1.90 degrees, Clay Loam soil texture, Migmatite geology, and mean NDVI of 0.115. The resulting Groundwater Potential Index (GWPI) ranged from 2.31 to 4.56, with a mean of 2.675. Classification into four groundwater potential zones revealed that Palladan is predominantly characterized by High potential (Zone 4), covering the majority of the study area, driven by favorable rainfall and exceptionally flat terrain. The study concludes that while Palladan possesses substantial groundwater recharge potential, projected increases in rainfall variability and land degradation under climate change scenarios pose significant long-term threats to recharge sustainability.

Keywords Groundwater recharge potential Climate change GIS based analysis Palladan Zaria.

Assessment of Electrical Power Quality Issues in Aircraft Dc System: Analysis of Voltage Drop and Harmonic Distortion

Alum Ikechukwu Otu — Department Of Postgraduate, Air Force Institute Of Technology Kaduna

Muyideen Omuya Momoh — Department Of Computer Engineering, Ahmadu Bello University, Zaria.

Princess Love David — Air Force Institute Of Technology Kaduna

Abdussalam El-suleiman — Air Force Institute Of Technology Kaduna

Gowon Sule — Air Force Institute Of Technology Kaduna

Godwin Eseosa Abbe — Air Force Institute Of Technology Kaduna

Kumater Peter Ter — Air Force Institute Of Technology Kaduna

The transition towards More Electric Aircraft (MEA) architectures, in which traditional hydraulic and pneumatic systems are replaced with electrical alternatives, has intensified reliance on aircraft DC electrical systems, making power quality essential for reliable operation. This study investigates the effects of voltage drop and harmonic distortion, two critical power quality issues in aircraft DC electrical systems and assesses the effectiveness of RC filtering as a mitigation approach. A simulation-based methodology was adopted, utilizing MATLAB/Simulink to model a representative aircraft DC distribution network. The model incorporated a DC source, distribution line impedance, variable resistive loads, and a subsystem for harmonic injection to emulate non-linear loads like power converters. The Simulation results showed that higher electrical loading brings about increased voltage drops and harmonic distortion, which adversely reduces power quality and voltage regulation. Under high-current (low resistance) conditions, voltage sagged significantly -voltage drop increased from 1.0 V at 25 Ω to 9.7 V at 5 Ω, and THD rose from 2.7% at 25Ω to 11.8% at 5Ω exceeding the 5% threshold at three lowest resistance cases, a level that is commonly flagged as a risk factor for sensitive equipment. To mitigate these issues, an RC filter was evaluated to improve power quality in aircraft DC distribution systems. The filtered configuration produced a visibly smoother, more stable load-voltage waveform relative to the unfiltered case, consistent with the expected attenuation behavior of a first-order low-pass filter. The study concludes that while load dynamics and non-linear components degrade power quality in aircraft DC systems, properly designed passive filters offer a simple and effective solution. These findings provide valuable insights for the design of more resilient and reliable electrical power systems, contributing to the safety and efficiency of next-generation More-electric and All-Electric Aircraft.

Keywords More-electric Aircraft Aircraft DC distribution Harmonic Distortion Voltage drop RC filtering Avionics

California bearing ratio of geopolymer-stabilized lateritic soil using sugarcane bagasse ash and rice husk ash as precursors

Aliyu Mani Umar — Ahmadu Bello University Zaria

Mustapha Amin Muhammad — Ahmadu Bello University Zaria

Ashiru Mohammed — Ahmadu Bello University Zaria

Nura Shehu Aliyu Yaro — Ahmadu Bello University Zaria

Yaseer Adam Nabage — Federal Polytechnic Bauchi

Adam Ado Sabari — The University Of Alabama In Huntsville

Surajo Abubakar Wada — Ahmadu Bello University Zaria

Environmental concerns coupled with economic considerations have heightened interests towards sustainable pavement construction. Several studies in sustainable pavement construction had explored stabilization of weak, unstable or problematic soils using agricultural wastes. Agricultural waste materials such as sugarcane bagasse ash (SBA) and rice husk ash (RHA) are rich in reactive silica and possess considerable pozzolanic potential, making them promising geopolymer precursors for soil stabilization. However, limited studies have investigated the combined performance of alkali-activated SBA and RHA in improving tropical lateritic soils used in road construction. This study evaluated the engineering performance of geopolymer-stabilized lateritic soil incorporating SBA and RHA activated with 1% sodium hydroxide. Lateritic soil (having silica-sesquioxide ratio of 1.41) obtained from Ahmadu Bello University Teaching Hospital (ABUTH), Shika, Nigeria, was stabilized using three SBA:RHA blends (3:1, 2:2, and 1:3), while soil stabilized with 4% Portland limestone cement served as the control. Laboratory tests included particle size distribution, specific gravity, Atterberg limits, X-ray fluorescence (XRF), compaction characteristics, and California Bearing Ratio (CBR) in accordance with BS 1377-2:2022. The natural soil was classified as A-7-5 under AASHTO and CL under the Unified Soil Classification System, indicating poor engineering quality. XRF analysis confirmed high silica contents in both ashes, particularly RHA (73.76% SiO₂), supporting their suitability for geopolymerization. Among the geopolymer mixtures, the 3:1 SBA : RHA blend achieved the greatest reduction in plasticity index (28.57% to 18.95%) and the highest unsoaked CBR of 66.5%, indicating significant improvement in bearing capacity. Stabilized specimens exhibited slightly higher optimum moisture contents (17-18%) while maintaining comparable maximum dry densities (1.83–1.86 Mg/m³). The results showed that alkali-activated SBA-RHA geopolymer is a viable and sustainable alternative to conventional cement stabilization for enhancing tropical lateritic soils for pavement applications.

Keywords Lateritic soil Geopolymer stabilization Sugarcane bagasse ash Rice husk ash Sustainable pavement California Bearing Ratio

Climate-Resilient Infrastructure Design for Flood-Prone Nigerian Cities: A Case Study of Maiduguri, Borno State.

Yahaya Watafua — Nigerian Army University Biu

Okhiria Kenneth — Nigerian Army University Biu

Nigerian cities are facing increasingly severe flood disasters as climate change, rapid and poorly planned urbanization, and ageing or inadequately maintained infrastructure increase exposure to flood hazards. The 2022 floods alone claimed more than 600 lives and displaced about 1.4 million people. More recently, the September 2024 failure of the Alau Dam near Maiduguri, Borno State, caused extensive flooding across the city, displacing large numbers of residents and resulting in significant loss of life. This paper presents a conceptual and practice-oriented review of sustainable and climate-resilient infrastructure strategies for flood-prone Nigerian cities, using the Maiduguri flood disaster as a focused case study. Drawing on published hydrological studies, disaster-management reports and literature on green and resilient infrastructure, the paper develops a five-tier framework that integrates hazard assessment, resilient planning standards, engineering design principles, blue-green and conventional grey infrastructure, and institutional and community-based measures. The Maiduguri case demonstrates how prolonged dam siltation, inadequate maintenance and weaknesses in infrastructure management can increase the consequences of extreme flooding, particularly in a city already affected by conflict and displacement. The paper argues that building flood resilience in semi-arid, inland and conflict-affected Nigerian cities requires more than sustainable drainage systems and nature-based flood defences. It also requires effective dam-safety management, regular infrastructure inspections, timely maintenance, reliable funding and stronger coordination among responsible institutions. The study concludes with practical recommendations for engineers, urban planners and policymakers to support climate-resilient infrastructure development and strengthen Nigeria’s capacity to adapt to increasing flood risks.

Keywords climate-resilient infrastructure dam safety flood risk management sustainable urban drainage maiduguri

COMPARATIVE ASSESSMENT OF PAVEMENT DISTRESS USING CONVENTIONAL MEASUREMENTS AND UAV PHOTOGRAMMETRY ALONG THE GOMBE - KWAMI HIGHWAY, NIGERIA

Salisu Ibrahim — Nbrri

Aminu Suleiman — Bayero University Kano

Accurate pavement distress assessment is essential for effective highway maintenance and transportation infrastructure management. Conventional pavement inspection methods are widely employed but are often labor - intensive, time - consuming, and susceptible to human error. This study evaluates the applicability of Unmanned Aerial Vehicle (UAV) photogrammetry for pavement distress assessment along the Gombe - Kwami Highway in Gombe State, Nigeria. Conventional field measurements and UAV photogrammetric surveys were conducted to determine pothole diameter, area, and depth. Statistical analysis including descriptive statistics, correlation analysis, paired sample t - tests, and mean percentage error, box plot, scattered plot and bar plot analysis were used to compare both measurement techniques. Results revealed strong agreement between conventional and UAV- derived measurements, with correlation coefficients ranging from 0.85 to 0.95 across the route. Mean percentage errors were generally below 4%, indicating acceptable engineering accuracy. The UAV - based approach successfully identified all observed potholes while providing detailed three - dimensional surface representations and improved measurement consistency. The findings demonstrate that UAV photogrammetry is a reliable, efficient, and cost - effective alternative to conventional pavement distress assessment methods and has significant potential for routine highway condition monitoring in Nigeria. The study concluded that UAV photogrammetry provides rapid data acquisition and improved measurement consistency compared with the conventional methods. It is recommended that highway agencies should adopt UAV photogrammetry for routine pavement condition assessment, and integrate data driven into pavement management systems for improved maintenance planning.

Keywords Pavement distress UAV photogrammetry pothole assessment highway maintenance transportation engineering.

Container - Water Interaction: Modeling Physicochemical and Microbial Changes During 14 Day Storage in Clay and Plastic Containers

Aminu Ohueyi Ahmed — Ahmadu Bello University, Zaria, Nigeria

Mohammed Aliyu Aliyu — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria, Nigeria

Mohammad Shamsuddeen Jumande — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria, Nigeria

Akinola Abdulwasiu Olalekan — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria, Nigeria

Access to safe drinking water remains a critical challenge in many regions, especially in developing countries where improper storage can degrade water quality. This study examines the effect of storage container type and duration on the quality of water obtained from different sources: rain, well, and borehole. The investigation centers on how clay pots and plastic containers affect physicochemical and biological parameters, including temperature, pH, turbidity, electrical conductivity (EC), total dissolved solids (TDS), dissolved oxygen (DO), and biochemical oxygen demand (BOD), over a 14-day storage period. Water samples were collected from selected sites in Zaria, Kaduna State, and subjected to laboratory analyses in accordance with standard procedures. Results revealed that both the type of container and the storage duration affect water quality. Prolonged storage led to a general decrease in DO and an increase in BOD, turbidity, and TDS, indicating microbial activity and chemical interaction with container materials. Clay pots maintained better water quality than plastic containers due to their porous structure, which allowed limited aeration and temperature regulation, thereby reducing microbial growth. Conversely, plastic containers showed greater chemical leaching and microbial proliferation, resulting in faster deterioration of water quality. Among the water sources, borehole water exhibited the highest physicochemical stability, followed by well water and rainwater, which displayed the greatest variation due to their low buffering capacity. The study concludes that water quality deteriorates with longer storage time, and the extent of deterioration depends on the storage material. It recommends using clay pots for short- to medium-term storage. It emphasizes the importance of regular cleaning, reduced storage time, and awareness of safe water handling to minimize contamination and health risks.

Keywords water storage clay pots plastic containers physicochemical parameters microbial activity water quality deterioration storage duration.

Deep Learning Prediction of Remaining Useful Life for Turbofan Engine using Attention Augmented LSTM Based Network

Oluwafemi Daniel Oluwapelumi — Air Force Institute Of Technology Kaduna/aerospace Engineering Department

Samuel David Iyaghigba — Air Force Institute Of Technology Kaduna

Marcus Aul Maafan — Air Force Institute Of Technology Kaduna/aerospace Engineering Department

Sadiq Thomas — Nile University Of Nigeria Abuja/dept Of Computer Engineering

Abbas Abdullahi — Air Force Institute Of Technology Kaduna/aerospace Engineering Department

Aircraft systems are complex networks of components that support the entire mission and functionality of an aircraft. These complex engineered systems play fundamental roles in providing critical services, particularly regarding air transportation and energy needs. Among these, turbofan engines are the primary power source. As the usage of these complex engineering systems expands, they are increasingly subjected to harsh operational environments. These conditions inevitably make them susceptible to mechanical faults that, if not detected early, can result in catastrophic failure. Notably, the turbofan engine has accounted for 60% of airplane failures during flight. Therefore, Prognostics and Health Management technology utilizing deep learning is essential for predicting the Remaining Useful Life of these systems. This study explores a Long Short-Term Memory network integrated with a sliding-window approach and a Temporal Attention mechanism to estimate engine operational lifespan. Unlike existing literature reliant on legacy benchmarks, this model is trained and validated on a high-fidelity dataset generated using AGTF30, a NASA-developed turbofan simulation environment; because RUL is measured in seconds rather than operating cycles, comparison against C-MAPPS-based literature is limited to relative RMSE rather than direct numerical validation. By extracting temporal degradation features from raw multivariate sensor data, the framework achieves an overall Root Mean Square Error of 249.0 seconds and, crucially, a near-failure RMSE of 39.3 seconds, demonstrating highly reliable predictive capability during critical terminal degradation phases.

Keywords Turbofan Engine Predictive Maintenance Remaining Useful Life LSTM Model Deep learning approach

Design and Performance Evaluation of a Dual-Media Filtration System Using Palm Kernel Shell Activated Carbon for Wastewater Treatment

Aminu Ohueyi Ahmed — Ahmadu Bello University, Zaria, Nigeria

Mohammed Aliyu Aliyu — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria, Nigeria

Abdullahi Mohammed Dalhatu — Samaru College Of Agriculture, Division Of Agricultural College, Ahmadu Bello University, Zaria, Nigeria.

Abdullahi Umar — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria, Nigeria

Yakubu Joseph Nlira — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria, Nigeria

The increasing demand for cost-effective and sustainable wastewater treatment technologies in developing regions has necessitated the exploration of locally available materials for tertiary treatment applications. This study presents the design and performance evaluation of a laboratory-scale dual-media filtration system incorporating palm kernel shell-derived activated carbon (PKS-AC) and sharp sand for the treatment of effluent from the Ahmadu Bello University (ABU), Zaria stabilization pond. The filtration column was constructed using a layered configuration of coarse sand, activated carbon, and fine sand to facilitate combined processes of physical filtration and adsorption. Wastewater samples were collected from the stabilization pond's final discharge point and analyzed before and after filtration for selected physicochemical parameters, including turbidity, nitrate concentration, biochemical oxygen demand (BOD), chemical oxygen demand (COD), and total dissolved solids (TDS). The results indicate substantial improvements in effluent quality after treatment. Turbidity was reduced from 13.0 NTU to 2.6 NTU, nitrate concentration decreased from 35.0 mg/L to 15.6 mg/L, COD was lowered from 3000 mg/L to 800 mg/L, and BOD decreased from 150 mg/L to 90 mg/L. Additionally, a moderate reduction in TDS was observed. The enhanced performance of the system is attributed to the synergistic interaction between the sand filtration layers and the adsorption capacity of PKS-AC. The findings demonstrate that the developed dual-media filtration system offers an efficient, low-cost, and sustainable solution for tertiary wastewater treatment, particularly in institutional and resource-constrained environments.

Keywords Dual-media filtration Palm kernel shell Activated carbon Wastewater treatment Adsorption Sand filtration

Design Optimisation and Impact Assessment of a Biogas-Integrated Anaerobic Baffled Reactor Wastewater Treatment System at Ikoyi Correctional Centre, Lagos, Nigeria

Philip Balogun — P&a Consulting Ltd

Philip Balogun — Department Of Water Resources And Environmental Engineering, Faculty Of Engineering, Ahmadu Bello University, Zaria, Nigeria

Donatus Begianpuye Adie — Department Of Water Resources And Environmental Engineering, Faculty Of Engineering, Ahmadu Bello University, Zaria, Nigeria

Igboro Sunday Bamidele — Department Of Water Resources And Environmental Engineering, Faculty Of Engineering, Ahmadu Bello University, Zaria, Nigeria

Aliyu Adamu Dandajeh — Department Of Water Resources And Environmental Engineering, Faculty Of Engineering, Ahmadu Bello University, Zaria, Nigeria

High-density correctional facilities face combined pressures of wastewater pollution, sanitation risk and cooking-energy demand, yet many interventions are assessed only as infrastructure projects rather than integrated environmental-management systems. This study presents the impact assessment and design optimisation of a biogas-integrated anaerobic baffled reactor (ABR) wastewater treatment system at Ikoyi Correctional Centre, Lagos, Nigeria. The work used project-derived wastewater laboratory results, geotechnical investigation records, design population data, ABR sizing outputs, biogas monitoring evidence, kitchen-energy estimates and financial indicators to evaluate system performance and identify optimisation requirements. The facility was designed for 3,000 users and an estimated sewage flow of 154.45 m³/day, split between two ABR trains. Baseline wastewater was highly polluted, with chemical oxygen demand (COD) of 2,278 mg/L, biochemical oxygen demand (BOD) of 569.5 mg/L and total suspended solids of 1,412 mg/L, confirming the need for engineered treatment. The ABR design achieved a hydraulic retention time of 52.42 h and predicted COD removal of 88%; however, the projected effluent COD of 274.59 mg/L and BOD of 56.12 mg/L remained above target limits of 200 mg/L and 50 mg/L, respectively, indicating the need for secondary polishing. Biogas production was estimated at 77.36 m³/day on average and about 96.3 m³/day at peak design condition, while monitoring indicated approximately 90 m³/day of steady production. The system eliminated manual faecal evacuation, improved sanitation, supported renewable cooking energy and generated reported financial benefits through reduced sewage evacuation and fuel substitution. The study proposes an optimisation framework covering effluent polishing, gas-utilisation capacity, digestate quality monitoring, gas safety, burner adequacy, preventive maintenance and hybrid energy planning. The findings demonstrate how engineering innovation can transform custodial wastewater into a sanitation, energy-recovery and sustainability intervention aligned with Nigeria’s sustainable development priorities.

Keywords Anaerobic baffled reactor biogas wastewater treatment design optimisation correctional facility sustainable environmental management Ikoyi renewable energy recovery

Designing Enforcement for Safety, Not Hazard: Evidence from a Traffic Management System Failure in Kano Metropolis

Muwaffaq Safiyanu Labbo — Aliko Dangote University Of Science And Technology

Muwaffaq Safiyanu Labbo — Aliko Dangote University Of Science And Technology, Wudil

Abubakar Idris — Aliko Dangote University Of Science And Technology, Wudil

Surajo Wada — Ahmadu Bello University, Zaria

Traffic enforcement is a core component of urban traffic management systems, yet its design is rarely subjected to the same safety-engineering scrutiny applied to road geometry, signal timing, or vehicle standards. This paper argues that it should be. Drawing on evidence from Kano metropolis, Nigeria, where traffic management relies heavily on contact-based enforcement by the Kano Road Traffic Authority (KAROTA), the study demonstrates that an enforcement subsystem designed around revenue generation rather than safety outcomes can itself become a source of crash risk. A survey of 331 urban drivers found that higher self-reported compliance with traffic regulations was independently associated with greater, not lower, crash involvement (OR = 1.72, p = .007), while perceived importance of regulation was independently protective (OR = 0.48, p < .001). The two were statistically unrelated. An attitude–behavior congruence typology revealed that drivers who always comply but do not value the rules, a profile consistent with coerced, surveillance-dependent compliance, recorded the highest crash rate (83%), while drivers who valued regulation but complied flexibly were safest (42%). Independently documented cases, including fatal “steering-drag” incidents, enforcement pursuits, and an informal “swap-driving” evasion system, corroborate the enforcement-as-hazard mechanism at the behavioral level. Institutional analysis traces the root to a revenue mandate, minimally trained personnel, and the absence of procedural safeguards. The paper concludes that safe traffic management system design must treat enforcement legitimacy as an engineering parameter: systems that substitute automated, infrastructure-based compliance mechanisms for discretionary contact-based enforcement, and that decouple enforcement from revenue incentives, are safer by design. Implications for the transition from contact-based to technology-enabled enforcement in Nigerian cities are discussed.

Keywords Traffic Management System Design Enforcement Safety Coerced Compliance Safe Systems Approach Kano Nigeria

DEVELOPMENT AND PERFORMANCE EVALUATION OF A WASTE PLASTIC SHREDDER

Akeem Adekunle Adebesin — Federal University Of Technology Ilaro

Ogundemuren Victor Oluwatobi — Department Of Mechanical Engineering, Federal University Of Technology, Ilaro

The increasing use of plastic materials in modern society has led to a significant rise in plastic waste generation. Improper disposal of these materials has created serious environmental challenges, particularly in developing countries where waste management systems are still evolving, hence plastic recycling has therefore become an important approach to reducing environmental pollution and promoting sustainable resource utilization. One of the key processes involved in plastic recycling is the reduction of plastic waste into smaller sizes that can be easily processed and reused. This paper focuses on the design and fabrication of a waste plastic shredding machine suitable for small and medium scale recycling operations. The machine was designed using fundamental principles of mechanical engineering and constructed using locally available materials to ensure affordability, durability, and ease of maintenance while the major components of the machine include the frame, hopper, shredding blades, shaft, drive mechanism, bearings, and a 6.5hp gasoline engine which serves as the power source. The machine operates on the principle of mechanical shearing and cutting, where plastic materials fed through the hopper are reduced into smaller particles by rotating blades mounted on a shaft. Performance evaluation of the fabricated machine was carried out using plastic waste materials and three experimental tests were conducted with an average plastic input weight of 5.37 kg and an average shredding time of 51.67 seconds. The results obtained showed an average shredded plastic output of 4.9 kg, resulting in a shredding efficiency of approximately 91.25 percent. The results indicate that the fabricated plastic shredding machine is capable of effectively reducing plastic waste into smaller particles suitable for recycling processes. The machine therefore provides a practical and cost-effective solution for improving plastic waste management and supporting environmental sustainability, especially in communities where recycling facilities are limited.

Keywords Plastics Environment Pollution Shredding Wastes Management Machine.

Development of an optimal Load Frequency Control strategy of the two-area power systems using Arithmetic Optimization Algorithm

Mustapha Abdullahi — Ahmadu Bello University Zaria

Sani Salisu — Ahmad Bello University Zaria

This study addresses frequency instability and tie-line deviations in interconnected power systems caused by sudden load perturbations. To overcome the slow recovery and transient instability of conventional PSO- and GA-tuned PID controllers, this research implements the Arithmetic Optimization Algorithm (AOA) for optimal Load Frequency Control (LFC) tuning. Using MATLAB/Simulink, a two-area power network was modeled and tested under step load disturbances of 0.2 p.u. and 0.15 p.u., using the Integral Time Absolute Error (ITAE) as the fitness criterion. The proposed PID-AOA controller significantly outpaced traditional methods, achieving a settling time of 5.22 s (a 43.68% improvement over PSO). Furthermore, the AOA yielded a superior fitness value of 0.04245 nearly seven times more efficient than PSO while successfully eliminating prolonged oscillations. Ultimately, the AOA-PID scheme delivers a robust, highly efficient solution that ensures superior transient stability and faster equilibrium recovery.

Keywords Arithmetic Optimization Algorithm load frequency control multi area power systems PID tie-line power

Effect of Base-seal on cement -Stabilized clayey Soil Admix with Rice Husk Ash (R.H.A)

Umar Mukhtar — Aliko Dangote University Of Science And Technology Wudil,kano State

Dr Gambo Haruna Yunusa — Bayero University Kano

Abdullahi Karaye — Bayero University Kano

Hassan Umar Sani — Umar Hassan Sani ,tiangong University China, School Of International Education Department Of Art Science

Hussein Umar Sani — Aliko Dangote University Of Science And Technology Wudil Kano

ABSTRACT
This study investigates the effect of base-seal on cement-stabilized clayey soil admixed with rice husk ash (RHA) for possible use in pavement construction. The research involved determination of index and engineering properties of the soil, as well as the chemical composition of Base-seal, Cement and Rice Husk Ash (RHA) Base-Seal. The soil sample was classified as A-6 according to the AASHTO classification system and CL according to the Unified Soil Classification System (USCS), The soil was mixed with 0–8% RHA and 1–4% cement Base-Seal was kept constant of dry weight of soil. Laboratory tests conducted include grain size analysis, Atterberg limits, compaction tests, California Bearing Ratio (CBR), Unconfined Compressive Strength (UCS). More over X-ray diffraction (XRD) analysis was performed to determine the mineralogical composition of the materials. The results showed a reduction in plasticity index and improvement in compaction characteristics with increasing RHA and cement contents and Base-Seal. The Maximum Dry Density (MDD) increased while the Optimum Moisture Content (OMC) decreased, indicating improved soil densification. Strength tests showed significant improvement in the California Bearing Ratio (CBR) values of Soaked and Unsoaked values 412.82% and 619.24% under British Standard Light (BSL), British Standard Heavy (BSH) comp active efforts, respectively, which complied with the Nigerian General specification for Roads and Bridge (1997) for soil-cement stabilization requirements for sub-base materials in highway construction (180% CBR). The Unconfined Compressive Strength (UCS) values at 28 days curing were under British Standard Light (BSL), British Standard Heavy (BSH) and compactive efforts, 1100 kN/m² and 1140 kN/m². The results demonstrate that combined use of soil-cement ,rice husk ash and Base-seal significantly improves the engineering properties of clayey soil, making it suitable for application in pavement construction.

Keywords Rice Husk Ash (RHA) Base seal Cement -Stabilized clayey

EFFECT OF MUNICIPAL SOLID WASTE LEACHATE ON PLASTICITY CHARACTERISTICS OF CLAY SOIL

Adamu Umar Chinade — Department Of Civil Engineering, Abubakar Tafawa Balewa University, Bauchi

Musa Umar Chinade — Department Of Architecture, Abubakar Tafawa Balewa University, Bauchi

Isa Zubairu — Department Of Civil Engineering, Abubakar Tafawa Balewa University, Bauchi, Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria Nigeria & Faculty Of Civil Engineering, University Teknologi Malaysia

Muhammad Abdu Nasara — Department Of Civil Engineering, Abubakar Tafawa Balewa University, Bauchi

Yakubu Hyelmura — Department Of Civil Engineering, Abubakar Tafawa Balewa University, Bauchi

The study investigates the effect of municipal solid waste leachate on the plasticity properties of clay soil. Dumping of solid waste on land is a common waste disposal method and is practiced by cities around some of the developing countries like Nigeria. Precipitation that infiltrates through the municipal solid waste leach the constituents from the decomposed waste mass and while moving down causes the surrounding soil to be contaminated by organic and inorganic constituents of the leachate altering the soil’s engineering properties. Specimens of clay soil were exposed to leachate contamination and plasticity characteristics including liquid limit, plastic limit, and shrinkage limits were determined. The contaminated clay specimens were cured for 7, 14, 21, 28, and 35 days respectively prior to testing. The result obtained showed that leachate significantly causes an increase in liquid limit and plasticity index of the soil indicating a potential decrease in strength and long-term stability. However, the plastic limits increase at the first instant (i.e 7 days to 14 days) and decrease as the contamination period increases beyond 14 days. The results indicated that MSW leachate can significantly affect the plasticity of soils which will subsequently alter the engineering behavior of such soils, therefore, the need for proper disposal and management of municipal solid waste in order to prevent soil contamination and associated environmental hazards.

Keywords Municipal solid waste Leachate Contamination Curing

Effects of hydrocarbon impurities on concrete strength and Durability: A comprehensive review.

Otu Nnamdi Johnson — Federal University Of Technology, Minna

James Olayemi James — Federal University Of Technology, Minna

Abubakar Mahmud — Federal University Of Technology, Minna

Concrete performance is significantly influenced by the quality of its constituent materials. In petroleum-producing regions, construction materials are frequently contaminated with hydrocarbons such as diesel and crude oil, leading to compromised structural integrity. This review critically examines the effects of hydrocarbon impurities on concrete strength and durability. It evaluates their influence on cement hydration, workability, compressive strength, and long-term durability. Findings reveal that hydrocarbons act as hydrophobic agents, disrupting bonding mechanisms and increasing porosity. The study also highlights mitigation strategies and identifies gaps for future research. This work provides a consolidated reference for engineers and researchers dealing with contaminated construction environments.

Keywords Concrete Hydrocarbon contamination Diesel compressive strength durability cement hydration.

Emerging Technologies for Safe Engineering Practices and Environmental Protection: A Systematically Informed, Evidence-Graded Review with a Proposed Nigerian Adoption Framework

Emmanuel Adie — Edo State University Iyamho

John Wasiu — Edo State University Iyamho

Ibrahim Abdulrazaq Olayinka — Edo State University Iyamho

Emerging technologies are reshaping engineering safety and environmental protection, yet evidence on their cross-sectoral effectiveness and applicability in resource-constrained economies remains fragmented. This study synthesises peer-reviewed evidence on artificial intelligence (AI), the Internet of Things (IoT), digital twins and BIM, virtual reality and sensor fusion, drones, and nanomaterials across construction, mining, and oil and gas operations. A systematically informed narrative-review approach was adopted, combining a reported search and screening process with manual verification and an operationalized evidence-grading rubric. An initial platform-assisted pool of 8,652,714 records from 23 searches and one citation-graph expansion was progressively screened to identify the final 37-study evidence corpus. The synthesis indicates the strongest convergent evidence for IoT- and AI-enabled monitoring and hazard detection, while evidence for digital twins/BIM, immersive technologies, and nanotechnology-based remediation remains comparatively limited. Reported quantitative effects of 18–22% risk reduction and 58–70% safety improvement are treated as single-case findings rather than generalizable technology effects. The study further develops a twelve-dimension, indicative Nigerian technology-adoption framework covering cost, infrastructure, skills, maintenance, regulatory readiness, data governance, cybersecurity, organisational readiness, technology maturity, and safety and environmental benefits. The framework is presented as an analytical proposition requiring empirical validation rather than as evidence of current Nigerian conditions. The findings support phased adoption of scalable monitoring and predictive technologies alongside strengthened regulatory, cybersecurity, occupational-exposure, and workforce-development measures.

Keywords emerging technologies engineering safety environmental protection artificial intelligence Internet of Things

Enhanced Anaerobic Digestion of Cow Dung and Poultry Dung Via a Coupled Microbial Electrolytic Cell: Optimization, Kinetics, and Thermodynamic Studies.

Ijuptil Ndumari — Ahmadu Bello University, Zaria

Olakunle Michael Sunday — Ahmadu Bello University, Zaria

Auwal Aliyu — Ahmadu Bello University, Zaria

Coupling a microbial electrolysis cell (MEC) with anaerobic digestion (AD) is an effective approach to improving methane yield from agricultural waste. The current research focuses on the optimization, kinetics, and thermodynamic analysis of the MEC–AD hybrid system using cow dung and poultry dung as substrates.
The physicochemical characterization results show that cow dung has higher volatile solids (78.20%) and a C:N ratio of 26.0, while poultry waste contains 62.35% volatile solids and a C:N ratio of 6.26. Based on mass balance calculations, the optimum substrate mixture containing 98.3% cow dung and 1.7% poultry dung is obtained to reach the optimum C:N ratio of 25:1.
The optimization process was carried out by applying Response Surface Methodology using Central Composite Design involving applied voltage (0.3–1.5 V), pH (6–8), and C:N ratio (15–35). The proposed quadratic equation showed a high prediction accuracy (R² = 0.9997) and obtained the optimum values of 0.97 V, pH 7.0, and C:N ratio of 25 with the optimum methane yield of 350.73 mL CH₄ g⁻¹ VS. Based on kinetic analysis using the modified Gompertz model, the ultimate methane potential, maximum methane production rate, and lag phase were found to be 378.33 mL CH₄ g⁻¹ VS, 41.25 mL CH₄ g⁻¹ VS day⁻¹, and 1.36 days, respectively. Thermodynamic analysis showed that the process achieved 91.02% energy efficiency, 73.8% exergy efficiency, and an EROI of 29.55, confirming its favorable energetic and thermodynamic performance.
Overall, the hybrid MEC–AD process significantly improved the methane yield.

Keywords Anaerobic digestion microbial electrolysis cell methane production Response Surface Methodology thermodynamic analysis

Flood Inundation Risk Assessment of An Earthen Dam Under Piping Failure Using HEC-RAS And QGIS: A Case Study of Kubanni Dam Zaria, Nigeria.

Aliyu Yahaya Muhammad — Ahmadu Bello University Zaria

Auwal Jarmai Babagirei — Ahmadu Bello University Zaria

Alamin Danladi Bello — Ahmadu Bello University Zaria

Khalid Sulaiman — Ahmadu Bello University Zaria

Abdulaziz Imam Ahmad — Ahmadu Bello University, Zaria

Raji Olasunkanmi Sheriffdeen — Federal University Oye-ekiti

This study presents the flood inundation risk evaluation of the dam formerly called Kubanni, an earthen dam with a water catchment area of 57 km2, situated in Zaria area, Kaduna State, Nigeria. The research aims to explain the pattern of dam breach by modeling it in three different return periods, (30, 50, and 100 years) and the hazard posed by the dam. HEC-RAS with QGIS software was used to run unsteady flow simulation of the dam break for piping failure. The breach parameters like the width of the bottom, the slope on the sides, and the time to formation were all obtained using empirical regression equations of Froehlich (2008), and as a result, the downstream hazard was mapped in several risk zones. The discharges during breach were 1,426.56m3/s, 1,697.71 m3/s, and 1,758.04 m3/s respectively for the three events. The flood events lasted for approximately 1 hour (30 and 50 year return periods) and 3 hours (100-year return period). The floodwater covered a distance of more than 10 km with Zango, Hanwa, Yan Karfe, and parts of Northeast Tudun Wada showing high flood vulnerability. Approximately 2,705 residences and several croplands located along the floodplain are in great danger from floods across 11 risk zones. The flood water took the minimum time of 10 sec reaching the nearest zone against the farthest zone where the water reached after 20min at the fastest depth level of 16.3m. These findings can assist dam safety management, land use regulation, and even the establishment of an early warning system at community level in other regions with similar challenge not monitored well.

Keywords Dam-break modelling Flood inundation HEC-RAS Flood hazard mapping Piping failure ABU Dam

Geo-spatial 2D analysis of Anthropogenic Heavy Metal Sources and Distribution in Soil and Groundwater In Funtua, Katsina State

Al-mustapha Abubakar — Department Of Water Resources And Environmental Engineering, Faculty Of Engineering. Ahmadu Bello University, Zaria

Aliyu Ishaq — Ahmadu Bello University, Zaria

Badruddeen Saulawa Sani — Department Of Water Resources And Environmental Engineering, Faculty Of Engineering Ahmadu Bello University, Zaria

Umar Alfa Abubakar — Department Of Water Resources And Environmental Engineering, Faculty Of Engineering Ahmadu Bello University, Zaria

Abubakar Sadiq Isah — Department Of Civil Engineering, Baze University, Abuja-nigeria

Heavy metal contamination of soil and groundwater is an escalating environmental and public health threat in rapidly urbanizing settlements, where overlapping anthropogenic activities complicate risk assessment and constrain effective management. In Funtua, Katsina State, Nigeria, limited geospatial evidence linking contamination sources to observed pollution patterns has hindered evidence-based groundwater conservation. This study spatially characterized anthropogenic heavy metal contamination in soil and groundwater across Funtua metropolis and identified priority zones for intervention. An integrated geospatial framework combining field surveys, systematic sampling, and atomic absorption spectrophotometry was employed. Concentration profiles, source-clustering patterns, contamination levels, and composite indices were computed and mapped using a Geographic Information System. Anthropogenic pollution sources exhibited statistically significant spatial clustering, including auto-mechanic workshops (z = −11.10), filling stations (z = −12.36), and dumpsites (z = −19.84), all at p < 0.001. Soil concentrations ranged from 0.19–0.26 ppm (Cd), 1.80–3.02 ppm (Cu), 1.74–7.46 ppm (Pb), 4.41–18.90 ppm (Fe), and 0.14–0.84 ppm (Ni). Groundwater analysis revealed markedly elevated lead (up to 74.37 ppm) and nickel (up to 560.10 ppm), exceeding permissible limits at several locations. The Metal Index (MI) ranged from 0.02 to 63.86, with 12.40% of the study area (17.09 km²) classified as contaminated; high-risk zones, though limited to 0.56% of the area, coincided with dense source overlap. Heavy metal contamination in Funtua is spatially structured and driven primarily by clustering of anthropogenic activities. Targeted monitoring, land-use control, and regulatory enforcement at identified hotspots are recommended, alongside a proposed low-cost biochar-based groundwater treatment system.

Keywords Heavy metal contamination Anthropogenic sources Soil pollution Groundwater quality Geospatial analysis

Hydrodynamic Assessment of Piping-Induced Dam-Break and Downstream Flood Hazard Classification at Zobe Dam, Nigeria. An integrated HEC-HMS and HEC-RAS Modeling Approach

Abdulaziz Imam Ahmad — Ahmadu Bello University, Zaria

Umar Abdullahi — Ahmadu Bello University, Zaria

Mohammad Shamsuddeen Jumande — Wree Department Ahmadu Bello University, Zaria

Raji Olasunkanmi Sheriffdeen — Federal University Oye-ekiti

Mohammed Aliyu Aliyu — Department Of Wree, Ahmadu Bello University, Zaria.

Aliyu Yahaya Muhammad — Ahmadu Bello University Zaria

Auwal Jarmai Babagirei — Ahmadu Bello University Zaria

Dam infrastructure occupies a central position in water resource management; and dam failure can produce severe consequences, especially in data-scarce regions where observed hydrological and failure data are limited. This study assesses a hypothetical piping failure of Zobe Dam, an earthen embankment with a documented history of seepage on the Karaduwa River in Katsina State, Nigeria, utilizing coupled HEC-HMS and 2D HEC-RAS modelling software. A terrain-delineated HEC-HMS model comprising five subbasins and two Muskingum-Cunge-routed reaches was used to generate inflow hydrographs for 30-, 50-, and 100-year design storms. Global Curve Number 250 (GCN250)-derived curve numbers and Soil Conservation Service (SCS)-derived lag times were used for hydrologic simulation, while breach parameters were estimated using Froelich (2008) formulation. Breach initiation was fixed at the documented Full Supply Level of 493.00 m across all scenarios. Peak basin-outlet discharge increased from 4,616.3 to 5,333.4 m3/s between the 30- and 100-year events, while peak breach discharge increased from 2,377.24 to 2685.35 m3/s. Flood depth, velocity, and inundation extent were from RAS Mapper and mapped in QGIS, with downstream hazard classified using the Australian Institute for Disaster Resilience (AIDR) Guideline 7-3 depth-velocity framework. Hazard classification remain unchanged across the three scenarios: Garhi was classified H6; Hakazama, Safana and Kunamawa as H5; and Dogon Ruwa and Makwanshi as H2/H3. The Water Treatment Plant and Bodole remained outside the modeled inundation extent. Sensitivity testing indicated limited variation in routed and breach discharges within the tested parameter ranges, while floodplain roughness produced a localized change in hazard classification at Safana. Garhi and the downstream road corridor linking Dutsin-Ma toward Kankara were identified as priorities for emergency preparedness and evacuation planning.

Keywords dam breach piping failure internal erosion HEC-RAS HEC-HMS flood hazard mapping design-storm rainfall Zobe Dam

IINFLUENCE OF SLICE THICKNESS AND DRYING TEMPERATURE ON THE PROXIMATE COMPOSITION OKRA: IMPLICATIONS FOR NUTRITIONAL QUALITY AND DRYING PROCESS OPTIMIZATION

Muhammad Mujahid Muhammad — Ahmadu Bello University, Zaria - Nigeria

Abba Yahaya — Ahmadu Bello University, Zaria - Nigeria

Mohammed Abdulsalam — Ahmadu Bello University, Zaria - Nigeria

Al-amin Danladi Bello — Ahmadu Bello University, Zaria - Nigeria

Daniel Onwude — Swiss Federal Laboratory Of Material Science And Technology, Empa, Switzerland.

Ibrahim Dalha — Ahmadu Bello University, Zaria - Nigeria

Mohammed Bashir Abdulrazaq — Ahmadu Bello University, Zaria - Nigeria

Badruddeen Saulawa Sani — Ahmadu Bello University, Zaria - Nigeria

Abdullahi Argungu Sule — Ahmadu Bello University, Zaria - Nigeria

Okra (Abelmoschus esculentus L. Moench) is a nutrient-dense vegetable with high moisture content that makes it highly perishable after harvest. Drying is thus a vital preservation technique, although processing conditions can change its nutritional composition. This study evaluated the effect of slice thickness and drying temperature on the proximate composition of okra. Okra samples of 0.5, 1.0, 1.5 and 2.0 cm thicknesses were subjected to processing temperatures of 30, 50, 60 and 70°C, with three replicates for each treatment combination represented by samples A, B and C. Moisture, ash, lipid, protein, fibre and carbohydrate contents were determined and expressed as percentages. Across all 45 observations, mean moisture, ash, lipid, protein, fibre and carbohydrate contents were 12.51, 8.91, 4.82, 16.70, 7.61 and 57.05%, respectively. The highest mean protein content (20.22%) occurred at 1.5 cm thickness and 60°C, while the highest mean fibre content (8.75%) was also recorded at this treatment. The maximm mean carbohydrate content (63.02%) occurred at 0.5 cm and 50°C, whereas the highest mean lipid content (6.90%) occurred at 2.0 cm and 70°C. The results establish substantial variation in proximate composition with processing temperature and sample thickness, indicating an interaction between the two factors. A thickness of 1.5 cm combined with 60°C produced a particularly favourable protein- and fibre-rich profile. The findings provide a useful guidance for selecting processing conditions for nutritionally desirable dried okra products.

Keywords Okra drying temperature sample thickness proximate composition

IMPACT OF AGEING WATER INFRASTRUCTURE ON WATER SUPPLY IN NIGER STATE:CASE STUDY OF SULEJA AND MINNA

Stephen Osu — Federal University Of Technolgy Minna

Mohammed Saidu — Federal University Of Technolgy Minna

Abstract: Ageing water infrastructure has become a major challenge to sustainable urban water supply in many developing countries, resulting in declining service reliability, increasing household dependence on alternative water sources and growing socio-economic burdens. This study assessed the impact of ageing water infrastructure on water supply reliability in Minna and Suleja, Niger State, Nigeria. Data were collected from 805 households (405 in Minna and 400 in Suleja), Niger State Water Board personnel, field observations, infrastructure inspections and secondary sources. Correlation and regression analyses were employed to evaluate the relationship between infrastructure condition and water supply reliability. The findings revealed that boreholes constitute the dominant household water source, while dependence on public piped water has declined because of deteriorating infrastructure. Minna consistently recorded better infrastructure condition, higher reliability, shorter water collection distance and lower household water expenditure than Suleja. Statistical analyses established a significant positive relationship between infrastructure condition and water supply reliability, indicating that deteriorated pipelines substantially reduce service continuity and increase household dependence on expensive alternative water sources. The study concludes that ageing infrastructure is the principal factor limiting sustainable urban water supply in Niger State with the correlation of 0.80 and 0.75 for Minna and Suleja respectively. It recommends systematic infrastructure rehabilitation, preventive asset management, expansion of distribution networks, continuous water quality monitoring and greater investment in modern water infrastructure to improve service reliability and achieve sustainable urban water management.

Keywords Ageing infrastructure water supply reliability

IMPACTS OF ROAD CONSTRUCTION SITE ACTIVITIES ON THE OCCURRENCE OF ACCIDENTS: A CASE STUDY OF THE ZARIA–KADUNA ROAD

Muhammed Mustapha Musa — Ahmadu Bello University, Zaria

Kasimu Yusuf Gojara — 2department Of Civil Engineering, Pan African University Institute For Basic Sciences, Technology And Innovation Kenya.

Ibrahim Bello — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria

Yusuf Ya'u — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria

Road transportation remains the dominant mode of movement for passengers and freight in Nigeria. Although road construction and rehabilitation projects are undertaken to improve transport efficiency, they often introduce temporary hazards within construction work zones. This study examined the impact of road construction site activities on the occurrence of road traffic accidents along the Zaria–Kaduna Road. The rehabilitation contract commenced in May 2018 and the Zaria–Kaduna section was completed in December 2022; the FRSC crash records analyzed cover the years 2017–2020, being the data available at the time of the study. A descriptive survey design was adopted, combining structured questionnaires, field observations and interviews with road users, contractor staff and FRSC officers. Poor road condition, illiteracy of both road users and workers, faulty vehicle condition, and driver behaviour emerged as the most common causes of accidents, each with a mean rating of at least 3.50 It is deduced, that from year 2018, 2020, an average of 2,612 persons were injured and 399 killed annually. The highest monthly figures rose from 147 injured and 18 killed in October 2017 (before commencement) to 213 injured and 43 killed in October 2018 (after commencement) increase of 45% and 139% respectively. The study recommends regular safety training for workers and road users, greater attention to health and safety by contractors and other stakeholders, consistent implementation of traffic-management plans on construction sites, and stricter enforcement of regulations.

Keywords Road construction work-zone safety road traffic accidents highway construction Zaria–Kaduna Road.

Infrastructure Characterization and Physical Integrity Assessment of Urban Water Distribution Systems: A Risk-Based Framework for Sustainable Asset Management in Minna, Nigeria

Abdulrahman Aminu — Ahmadu Bello University, Zaria

Johnson A. Otun — Ahmadu Bello University, Zaria

Aliyu Ishaq — Ahmadu Bello University, Zaria

Abstract
Nigerian water utilities have invested heavily in expanding treatment capacity while distribution pipe networks keep ageing largely unexamined. Minna's municipal system, run by the Niger State Water and Sewage Corporation (NISWASEC), illustrates this: demand has outgrown the network's design capacity, and pipeline failures, leakage, and pressure problems have followed. Detailed condition-assessment tools remain out of reach for NISWASEC, so rehabilitation relies on institutional memory and emergency logs rather than systematic condition assessment. This study addresses that gap by developing a GIS-supported Physical Integrity Index (PII) combining four engineering indicators, pipe age, failure frequency, leakage density, and coverage efficiency, applied across Minna's seven service clusters using maintenance records, field surveys, and staff interviews, validated through sensitivity and correlation analysis. Computed PII values ranged from 2.22 in Bosso (Moderate Integrity) to 4.55 in Minna West (Critical Integrity), with three clusters accounting for 53.6% of 6,527 pipeline failures logged between 2021 and 2025. Cluster rankings were consistent across three alternative weighting scenarios, and PII correlated strongly with recorded failures (r = 0.961) and service coverage (r = -0.871). The framework gives NISWASEC an evidence-based way to see where its network is failing rather than reacting to whatever breaks next, and should transfer to other medium-sized utilities facing similar constraints. NISWASEC should direct rehabilitation funding first to Minna West and Minna East, adopt the PII as a routine annual assessment, and begin disaggregating maintenance expenditure and non-revenue water by cluster.

Keywords Physical Integrity Index water distribution network infrastructure asset management rehabilitation prioritization Nigeria

INTEGRATED EXERGETIC–ECONOMIC ASSESSMENT OF THERMAL AND CATALYTIC PYROLYSIS OF HOUSEHOLD THERMOPLASTIC WASTE FOR SUSTAINABLE WASTE-TO-ENERGY APPLICATIONS

Zhidaya Jude — Federal University Of Technology, Minna, Niger State

Eyitayo A. Afolabi — Federal University Of Technology, Minna, Niger State

O. S. Azeez — Federal University Of Technology, Minna, Niger State

The increasing generation of household plastic waste has created significant environmental, resource-management and energy-recovery challenges, particularly in developing countries. This study presents an integrated exergetic–economic assessment of thermal and catalytic pyrolysis of mixed household thermoplastic waste using Aspen Plus V14 The simulated feedstock comprised HDPE, LDPE, PE, PP, PS, PET and PVC at a processing capacity of 1,000 kg h⁻¹. Thermal pyrolysis was evaluated at approximately 500°C, while catalytic pyrolysis employed ZSM-5 at approximately 350°C. The assessment integrated mass and energy balances, exergy analysis, techno-economic evaluation and Specific Exergy Costing (SPECO)-based exergoeconomic analysis. Thermal pyrolysis produced 65.2 wt% liquid oil, 19.8 wt% non-condensable gas and 15.0 wt% char,whereas catalytic pyrolysis produced 58.5 wt% liquid, 29.0 wt% gas and 12.5 wt% char. The catalytic configuration substantially increased the gas fraction and promoted the formation of lighter and gasoline-range hydrocarbons. The reported energy analysis showed a lower energy requirement for catalytic pyrolysis, while exergetic efficiency increased from 62% for thermal pyrolysis to 71% for catalytic pyrolysis. Capital investment decreased from approximately US$5.04 million to US$4.00 million, while annual operating expenditure decreased from approximately US$1.86 million to US$1.21 million. The reported economic assessment indicated higher NPV, IRR, profitability index and shorter payback period for catalytic pyrolysis. SPECO analysis identified the drying stage as a major contributor to exergy-destruction cost, while catalytic operation substantially reduced combustor exergy-destruction cost. The findings demonstrate the potential of catalytic pyrolysis as an integrated thermodynamic and economically attractive pathway for converting household thermoplastic waste into valuable energy products.

Keywords household thermoplastic waste thermal pyrolysis catalytic pyrolysis ZSM-5 Aspen Plus exergy analysis exergoeconomics SPECO waste-to-energy

MINIMIZATION OF POWER LOSSES IN DISTRIBUTION NETWORKS THROUGH SMART GRID TECHNOLOGIES: A CASE STUDY OF BWARI 33 KV DISTRIBUTION NETWORK

Francis Igbinosa — University Of Abuja

Eronu Emmanuel — University Of Abuja

Dr. Ngang Bassey Ngang — University Of Abuja

This study presents a comprehensive modeling and simulation-based investigation aimed at minimizing technical power losses and enhancing voltage profiles within the Bwari 33 kV distribution network, representative of Nigerian urban power infrastructure. Utilizing MATLAB/Simulink, a detailed radial feeder model was developed, capturing realistic operational characteristics, including load composition, line parameters and substation configurations. The research employs a quantitative approach, uncooperative baseline analysis and scenario-based simulations to evaluate the effects of smart grid functionalities. Key system parameters considered include voltage profile, active and reactive power losses, circuit breaker loading, thermal effects and overall network efficiency. The analysis revealed that overload conditions significantly increase technical losses due to the I2R relationship, resulting in higher active and reactive power losses, increased voltage drop and reduced system efficiency. To mitigate these effects, several smart grid technologies were evaluated, including Advanced Metering Infrastructure (AMI), Adaptive Protection and Distribution Automation (APDA), Volt-VAR Optimization (VVO), Battery Energy Storage System (BESS). Simulation results showed that individual smart grid technologies achieved loss reductions ranging from 10% to 30%, while coordinated smart grid operation reduced total energy losses from 15,581.20 MWh/day to 11,497.73 MWh/day, representing a 26.2% reduction in losses. The economic assessment further demonstrated the viability of smart grid implementation, with estimated annual savings of $179,024,314.72. In addition, the reduction in energy losses contributes to lower carbon emissions and improved environmental sustainability. The study concludes that the integration of smart grid technologies provides an effective and economically feasible solution for minimizing power losses, improving voltage regulation, enhancing system reliability and reducing overload-induced stress in distribution networks. It is therefore recommended that power utilities adopt a phased approach to smart grid implementation to enhance the operational performance and sustainability of modern distribution systems.

Keywords Power Loss Minimization 33 kV Distribution Network Overload Conditions Circuit Breaker Overload Protection Simulation-Based Modeling Smart Grid Technologies Improved Environmental Sustainability.

Multivariate and Machine Learning-Based Assessment of Pore Pressure Dynamics for Dam Safety Monitoring: A Case Study of Gurara Dam, Nigeria

Ozomata Agoyi — Nuhu Bamalli Polytechnic

Muhammad Mujahid Muhammad — Ahmadu Bello University

Babatunde Karode Adeogun — Ahmadu Bello University

Abstract
Reliable interpretation of pore-pressure behaviour is essential for dam safety monitoring where hydraulic loading, delayed responses and spatially variable instrumentation coexist. This study develops a sensor- and zone-resolved multivariate framework for Gurara Dam, Nigeria, integrating Pearson correlation with false-discovery-rate (FDR) correction, partial correlation, cross-correlation lag analysis, Isolation Forest anomaly screening, XGBoost regression and principal component analysis (PCA). The monitoring network comprises 66 vibrating-wire piezometer cells, of which 63 were functional, distributed across five zones (CB, CC, CD, CR and CS). The dataset contains 136 approximately weekly observations from January 2022 to December 2024; 92 observations were used for chronological model development and 44 independent observations for 2024 testing. Reservoir level showed the strongest contemporaneous association with pore pressure in CS (r = 0.945, q < 0.001), followed by CR (r = 0.807) and CB (r = 0.774), while rainfall showed no significant contemporaneous zone-level association after FDR correction. Cross-correlation identified responses from 0 to 8 weeks, with the strongest lagged relationship at CB 16.15 (r = 0.981; 2 weeks). Independent-test XGBoost R² values were 0.823, 0.251, 0.645, 0.179 and 0.881 for CB, CC, CD, CR and CS, respectively. PCA showed a persistent dominant spatial-temporal mode, with PC1 explaining 50.86% – 57.21% of standardized variance and PC1–PC2 explaining 63.52% – 67.69%; interannual Tucker congruence was 0.89 – 0.93. The results demonstrate substantial spatial heterogeneity and support an integrated monitoring strategy combining statistical association, lag analysis, anomaly screening and sensor-specific prediction.

Keywords Pore pressure Gurara Dam piezometers PCA cross-correlation XGBoost Isolation Forest FDR correction contemporaneous

Non-Parametric Assessment of Wind-Sector and Elevation Effects on Contaminant Distribution around a Cement Factory

Taiwo Abadunmi — Division Of Agricultural Colleges, Ahmadu Bello University, Zaria

Ayodele Olanrewaju Ogunlela — Agricultural And Biosystems Engineering, University Of Ilorin

Kamorudeen Olaniyi Yusuf — Agricultural And Biosystems Engineering, University Of Ilorin

Contaminants released from industrial point sources can build up in air, soil and groundwater surrounding the source. A non-parametric statistical framework was used to assess the spatial distribution of contamination indicators for particulate matter (PM; n = 9), soil (n = 17), and groundwater (n = 52) around a cement factory. Most variables, especially in the soil and water, were significantly non-normally distributed as indicated by Shapiro-Wilk tests (p < 0.05) consistent with point-source deposition. Simple radial distance was insignificant (p > 0.05) for all matrices under the Spearman's rank correlation analysis, suggesting that radial distance alone is not a good predictor of contamination gradients. Stratifying by prevailing upwind/downwind sector greatly increased the correlations, particularly those for particulate deposition rate and weight (ρ = -1.000, p < 0.001), and between topsoil lead and potassium (ρ = -0.800); correlations were less significant for groundwater and remained low (ρ = -0.05 to -0.29) suggesting the soil column would act as a buffer to prevent vertical migration. The contamination of the topsoil was mostly independent of elevation, suggesting a depositional source from the atmosphere, while the contamination of the groundwater was significantly and negatively correlated with elevation (ρ = -0.3057; p = 0.049), suggesting that the Cd is accumulating in low-lying hydrological sinks driven by topography. Our results demonstrate that the use of directional and topographic sampling designs substantially improves gradient resolution over radial distance sampling designs, with relevance to environmental monitoring around point-source facilities.

Keywords Industrial point sources Spearman's rank correlation wind-sector stratification groundwater contamination cement industry

Optical Emission Spectroscopy (OES) Analysis of Corrosion of High-Grade Conventional 5 mm Ukrainian Metallic Plate Used in Tanker Truck Fabrication in Nigeria

Jamilu Haruna — Ahmadu Bello University Zaria

Abdulkareem Abubakar — Ahmadu Bello University Zaria

Usman Abubakar Zaria

Abdulmajid M. Nainna — Air Force Institute Of Technology Kaduna

Abubakar Ado Datti — Ahmadu Bello University Zaria

Elemental compositional analysis provides a metallurgical basis for interpreting corrosion severity in tanker steel beyond what mass-loss or electrochemical measurements alone can show. This research studies changes in the elemental composition of carbon steel metallic plate due to corrosion in PMS and AGO medium using bulk Optical Emission Spectroscopy (OES). The study considers control (unexposed), PMS-corroded and AGO-corroded coupons of high-grade conventional 5 mm Ukrainian carbon steel plate (4.5 mm actual thickness) used for tanker fabrication in Nigeria, following 63-day immersion at ambient temperature. OES showed a progressive decrease in iron content from >97.9 wt.% (control) to

Keywords Carbon steel OES elemental composition corrosion PMS AGO.

Performance Evaluation of Model Reference Adaptive Control for String Stability in Heavy-Duty Truck Platooning

Hassan Maharazu — Federal University Of Transportation Daura

Dr. Z. Haruna — Ahmadu Bello University Zaria

Dr. O. Ajayi — Ahmadu Bello University Zaria

Muktar Abubakar — Federal University Of Transportation Daura

Mohammed Babakolo Adamu — Federal University Of Transportation Daura

The deployment of heavy-duty truck platooning has gained considerable attention as an intelligent transportation solution capable of improving highway safety, fuel economy, and traffic efficiency. However, achieving string stability under varying operating conditions remains a critical challenge due to vehicle parameter uncertainties, external disturbances, communication delays, and nonlinear longitudinal dynamics, which can amplify spacing and velocity fluctuations throughout the platoon. This study presents a comprehensive performance evaluation of a Model Reference Adaptive Controller (MRAC) for enhancing string stability in heavy-duty truck platooning. The proposed control strategy employs a reference model to define the desired platoon dynamics, while a Lyapunov-based adaptive law continuously updates the controller parameters to compensate for system uncertainties and maintain stable vehicle-following behaviour. The controller is evaluated through MATLAB/Simulink simulations using a multi-vehicle platoon subjected to speed variations and disturbance scenarios. Performance is assessed using inter-vehicle spacing error, velocity tracking error, settling time, disturbance attenuation capability, and string stability characteristics, with comparisons made against a Distributed Model Predictive Control integrated with a Proportional–Integral–Derivative (DMPC–PID) controller. Simulation results demonstrate that the proposed MRAC effectively suppresses disturbance propagation along the platoon while maintaining the desired inter-vehicle spacing of 10 m and cruising speed of 20 m/s. The controller achieved an average spacing error of 0.15 m and an average velocity error of 0.13 m/s, with convergence to steady-state conditions within approximately 20 s. Comparative analysis indicates that the MRAC exhibits superior tracking accuracy, faster adaptation, enhanced robustness to parameter uncertainties, and improved string stability compared with the benchmark DMPC–PID approach. These findings demonstrate that MRAC provides an effective adaptive control framework for autonomous heavy-duty truck platooning operating under uncertain and dynamic driving environments, thereby contributing to the advancement of robust cooperative vehicle control systems for future intelligent transportation applications.

Keywords Keywords: String Stability Heavy-Duty Truck Platooning Adaptive Control Intelligent Transportation Systems (ITS) Longitudinal Vehicle Control

Probabilistic Frequency Estimation of Boiling Liquid Expanding Vapour Explosion in a Liquefied Petroleum Gas Add-On Skid System Using Integrated Fault Tree and Event Tree Analysis

Shuaibu Musa — Ahmadu Bello University, Zaria

Abdullahi, Nuraddeen Bakori — Department Of Chemical Engineering, Kaduna Polytechnic

Ibrahim A Mohammed-dabo — Department Of Chemical Engineering, Faculty Of Engineering, Ahmadu Bello University, Zaria, Nigeria

The catastrophic failure of LPG storage tanks is considered to be one of the most catastrophic hazards in the downstream segment of the gas sector but frequency calculations for LPG facilities in Africa are seldom carried out using formal reliability studies. In this paper, the frequency of occurrence of Liquid Expanding Vapour Explosion (BLEVE) accident of a small-scale 8.85 m³ LPG add-on skid unit has been determined using integrated Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) via Isograph Reliability Workbench v15.0 software package. A 12 basic event fault tree was developed for the top event of catastrophic rupture of the LPG bullet tank, utilizing mechanical, electrical and human errors based on failure statistics available from Offshore and onshore reliability data (OREDA), IEEE Std 493 and IEC 61511-1 standards in conjunction with AND and OR gate operations. Five simulation runs have resulted in the top event frequency of 0.7322 per year with main contributing factors being centrifugal pump mechanical seal failure (2.0×10⁻¹/yr), flame and gas detector failure (1.5×10⁻¹/yr) and pressure temperature transmitter failure (1.0×10⁻¹/yr). The event tree derived from the initiating event of the loading line rupture had five different pathways to either a safe dispersion, a flash fire, a vapour cloud explosion, a jet fire, and a BLEVE, with the BLEVE pathway having a conditional frequency of 4×10⁻²¹ per year if all active barriers are in working order. It can be seen that it is not enough for any single element to fail to cause the top event, but rather degradation of several barriers at once is necessary.

Keywords Fault tree analysis Event tree analysis BLEVE LPG storage Reliability data Isograph Reliability Workbench

Process Intensification of a 50 BPD Modular Mini-Refinery : A Simulation-Driven Pinch Analysis Approach for Enhanced Heat Recovery and Sustainable Refining in Nigeria.

Habib Ahmed Tijjani — Nigerian National Petroleum Company Limited

Ibrahim Mohammed-dabo — Chemical Engineering Department, Ahmadu Bello University, Zaria.

Waziri S. M. — Chemical Engineering Department, Ahmadu Bello University, Zaria.

Mustapha M. Sugungun — Nigerian National Petroleum Company Limited

The global drive toward distributed, small-scale petroleum refining has positioned modular mini-refineries as strategic assets for energy security in oil-producing developing economies. Yet, their widespread adoption in Nigeria remains constrained by simplistic process configurations, weak thermal integration, and heat exchanger networks designed without rigorous thermodynamic targeting, resulting in avoidable utility consumption, elevated operating costs, and diminished product value. While pinch-based energy integration is well established for large-scale refineries, its systematic coupling with commercial process simulation for sub-100 BPD modular systems has been sparsely addressed, constituting a distinct methodological gap that limits the energy-efficient scale-up of Nigeria's local refining capacity.
This work presents an original process integration and intensification framework for the Ahmadu Bello University Mini-refinery, transforming its existing 1 BPD topping unit into an optimized 50 BPD Atmospheric Distillation Unit processing a blend of Escravos and Forcados crude. Aspen HYSYS was applied for rigorous material and energy balancing, equipment sizing, and case-based yield optimization, with all simulation outputs cross-validated against independent manual calculations to within approximately 5% deviation, confirming model robustness.
Energy integration and optimization measurably improved naphtha, kerosene, and diesel recoveries while reducing residue generation, demonstrating tangible gains in crude value addition and heat recovery. By uniting simulation-driven design with structured heat integration at modular scale, this study delivers a novel, economically significant, and industrially replicable pathway toward sustainable, energy-efficient refining, directly advancing Nigeria's refining industry and supporting Sustainable Development Goals 7, 9, 12, and 13 through affordable clean energy, resilient infrastructure, responsible resource use, and climate-conscious industrial practice.

Keywords Process Intensification Energy Integration Pinch Analysis Heat Exchanger Network Mini-Refinery Optimization Sustainable Refining.

Spatial Variation Assessment of Groundwater Quality in Iwo Local Government Area, Osun State, Nigeria.

Yuusuf Adetona — Department Of Civil Engineering, University Of Ibadan, Ibadan, Nigeria

Kamar Taiwo Oladepo — Department Of Civil Engineering, Obafemi Awolowo University, Ile-ife, Nigeria

Groundwater is the primary water source for over 60 % of Nigerians, but uncontrolled urban pollution infiltrates and contaminates the aquifer. Groundwater samples for the current study were collected from Iwo Local Government Area to investigate groundwater resources and generate spatial water-quality variation maps across seasons. The groundwater samples were chosen to represent the entire study area's built-up portion adequately. The physico-chemical parameters were measured during the rainy and dry seasons. Parameters analysed were temperature, turbidity, pH, electrical conductivity, total suspended solids, total dissolved solids, total alkalinity, total hardness, chloride, sulphate, nitrate, phosphate, magnesium, total coliform, and calcium. The simple kriging interpolation method was used to generate groundwater quality maps for the selected groundwater quality parameters. The water quality data were linked to the sampling location (spatial) in ArcGIS, and maps were generated to show spatial distribution. Although most of the water quality parameters median range values of the various groundwater resources were satisfactory throughout the seasons, total hardness of 228.3 mg/l – 596.6 mg/l, calcium of 16 mg/l - 236.8 mg/l, sulphate of 219 mg/l – 354 mg/l, and phosphate of 0.30 mg/l – 3.42 mg/l were the groundwater quality parameters with spatial variations over the World Health Organisation standard values of 150 mg/l, 75 mg/l, 250 mg/l, and 0.05 mg/l respectively, for both rainy and dry seasons. It is suggested that all sources be monitored regularly and that treatments to improve total hardness be implemented.

Keywords Groundwater Quality Maps Simple Kriging Spatial Distribution Iwo Local Government Area Simple Kriging ArcGIS Analysis Total Hardness

Study of the Corrosion Rate of Nigerian High-Grade Conventional 5 mm Ukrainian Metallic Plate Using Weight Loss (Gravimetric) Method

Jamilu Haruna — Ahmadu Bello University Zaria

Abdulkareem Abubakar — Ahmadu Bello University Zaria

Usman Abubakar Zaria — Ahmadu Bello University Zaria

Abdulmajid M. Nainna — Air Force Institute Of Technology Kaduna

Abubakar Ado Datti — Ahmadu Bello University Zaria

Accurate estimation of corrosion rate is essential for predicting the service life of petroleum tanker materials, yet different measurement techniques can yield numerically different results depending on whether they capture average or instantaneous corrosion behaviour. This study used weight loss/Gravimetry technique in investigating corrosion of Nigerian carbon steel tanker truck material in AGO and PMS medium over full 63-day exposure. The gravimetric analysis revealed measurable degradation of the carbon steel coupons following immersion in both petroleum products. However, the degree of deterioration varied considerably between the two fuels. The AGO-exposed specimens recorded an average weight loss of 0.40 g, whereas the PMS-exposed samples exhibited a mean weight loss of 0.20 g. This indicates that the mass loss in diesel was approximately 100% greater than that observed in petrol under identical exposure conditions. The calculated corrosion rates followed the same trend. The average corrosion rate of 0.129 mm/year for AGO was approximately twice that obtained for PMS (0.065 mm/year). This clearly demonstrates that the carbon steel experienced a more aggressive corrosive environment in diesel than in petrol. The observed difference may be attributed to the chemical characteristics of AGO. Generally, AGO contains a greater proportion of high-molecular-weight hydrocarbons and, depending on its quality and storage conditions, may contain sulphur compounds, oxidation products, organic acids, dissolved oxygen, trace water, and microbial metabolites. These species can accelerate electrochemical corrosion processes, resulting in greater dissolution of the iron matrix than in PMS.

Keywords Corrosion rate weight-loss method ASTM G31 carbon steel PMS AGO.

A comprehensive review on the poultry brooding requirements and forced air methods of heat generation for brooding.

George Akwec — Federal University Of Technology, Minna

Adebayo Segun Emmanuel — Federal University Of Technology, Minna

Caroline Omoanatse Alenoghena — Federal University Of Technology, Minna

Brooding is among the most sensitive stages in the poultry production cycle because neonatal chicks bare premature thermoregulatory body systems making them rely totally on external sources of heat for growth and development however, the inadequacy and the inconsistency of the heat supply remain a major challenge as such, the design and construction of air heating system is vital in the chick’s production sector. This review discussed brooding requirements, chick behavior in response to environmental factors, influence of environmental factors on feed conversion efficiency, growth performance and mortality. Furthermore, different air heating systems and their operational principles including construction procedures, material selection, insulation and the recent development in forced-air heating technology are discussed. The study identified that Computational Fluid Dynamics is an important tool for optimization of aspects such as air flow, duct geometry and temperature distribution pattern. The study further identified the existing research gaps from where the corresponding future directions were suggested. The study concluded that, performance of the system doesn’t only rely on the heat source or mode of heat transfer but also on the construction workmanship while considering material selection and insulation.

Keywords brooding requirements forced air heating methods construction insulation material selection

Bioelectricity Generation and Nutrient Removal from Landfill Leachate Using Double-Chamber Microbial Fuel Cells

Aliyu Ishaq — Department Of Water Resources Faculty Of Engineering, Ahmadu Bello University

Ismail Shafiu Nuhu — Department Of Civil Engineering, Federal Polytechnic Daura Katsina State

Shamsuddeen Jumande Muhammad — Department Of Water Resources Faculty Of Engineering, Ahmadu Bello University

Jamila Baba Ali — Department Of Polymer And Textile Engineering, Ahmadu Bello University, Zaria, Nigeria

Kehinde Adeagbo — Department Of Water Resources Faculty Of Engineering, Ahmadu Bello University

Abstract
Landfill leachate is a high-strength, nitrogen-rich wastewater whose elevated ammonium nitrogen (NH4-N) content limits the performance of conventional biological treatment. Microbial fuel cells (MFCs) offer a means of simultaneously treating such leachate and recovering bioelectrical energy, but the concentration at which NH4-N begins to inhibit MFC function remains poorly defined. A laboratory-scale, double-chamber MFC system comprising an anodic and a cathodic compartment separated by a Nafion 117 proton-exchange membrane was evaluated using raw leachate from the Simpang Renggam landfill, Kluang, Johor, Malaysia. Seven H-type reactors (six inoculated units, MFC A–F, and an uninoculated control) were operated in fed-batch mode over four operational cycles (7–12 days each) to establish an electroactive anodic biofilm. Influent NH4-N concentration was then varied between 400 and 1600 mg/L using a one-factor-at-a-time (OFAT) protocol to identify the inhibitory threshold. During biofilm development, chemical oxygen demand (COD) removal reached a maximum of 80.10 ± 0.5% (Coulombic efficiency 12.04%) in MFC C, while NH4-N and total nitrogen (TN) removal in the same reactor peaked at 68.12 ± 0.0% and 58.76%, respectively both substantially higher than the control. Power density increased with NH4-N loading up to an optimum near 800 mg/L before declining progressively, confirming an ammonia-driven inhibitory effect on exoelectrogenic activity. Nitrogen was removed via parallel pathways, including a measurable anaerobic ammonium oxidation (anammox) contribution. Moderate leachate salinity (5.58 ppt) did not independently limit performance. MFC technology can achieve simultaneous organic-matter and nitrogen removal from landfill leachate with concurrent energy recovery, provided influent NH4-N is maintained below the inhibitory threshold identified here.

Keywords Microbial fuel cell Landfill leachate Ammonium nitrogen inhibition Anammox Bioelectricity generation.

Comparative CFD Analysis of Rib Architectures and Honeycomb Surfaces for Brake Drum Cooling

Jephthah Bwede — Ahmadu Bello University, Zaria

Prof. G. Y. Pam — Ahmadu Bello University, Zaria

Dr. U. Hassan — Ahmadu Bello University, Zaria

Lot Dambvo Yusuf — Ahmadu Bello University, Zaria

This paper presents a comparative study of rib architectures (straight-rib, curved-rib, and axial-rib) integrated with honeycomb structures to enhance the cooling of the Brembo 14.D637.10 brake drum. Simulations were performed using parameters for the 2024 Toyota Hilux, grey cast iron (EN-JL-1040) as the brake drum material and air properties typical of tropical regions. Results indicate that the curved-rib configuration produced the most balanced enhancement achieving a minimum temperature of 241.98 ℃ and 21.47 W/mm^2 in maximum total heat flux, a 56.33 % and 86.87 % thermal performance uplift respectively compared to the conventional brake drum. The axial-rib model demonstrated significantly higher cooling efficiency, with a recorded 17.85 ℃ in minimum temperature and 34.56 W/mm^2 in maximum total heat flux, a 2019.69 % and 91.84 % increase respectively in thermal performance. These findings also suggest that integrating biomimetic honeycomb structures can increase convective surface area by approximately 98.93 %, (5521 faces up from 104 faces) effectively addressing modern vehicular thermal demands.

Keywords Brake drum Thermal management Biomimetic honeycomb Computational fluid dynamics Forced convection

Conceptual Design, Operations, and Theoretical Modeling of a 1 kW Physical Scale Prototype for the Kainji Hydropower Dam

Abdurrasheed Said Abdurrasheed — Ahmadu Bello University, Zaria

Raphael Ejembi — Ahmadu Bello University, Zaria

Mujahid Muhammad Mujahid — Ahmadu Bello University, Zaria

Aliyu Ishaq — Ahmadu Bello University Zaria

Sambo Mohammed Aminu — Ahmadu Bello University, Zaria

Jamila Shuaibu — Ahmadu Bello University, Zaria

Williams Ejembi — Ahmadu Bello University

Islam Sajjad Muhammad — Ahmadu Bello University, Zaria

Physical scale models serve as vital bridge structures for connecting theoretical fluid dynamics with practical hydroelectric power generation. This paper conceptually introduces the design, operational mechanics, and theoretical foundations of the Kainji Hydropower Dam model—a functional physical testbed developed at Ahmadu Bello University, Zaria, in partnership with Mainstream Energy Solutions Limited. Geometrically scaled to mirror the low-to-medium hydraulic head characteristics of the actual Kainji Dam, the physical installation comprises an elevated impoundment reservoir, high-pressure penstock conduits, flow control gates, and 2 micro-turbines assembly coupled to a synchronous combine generation of 1kW.
The underlying theory integrates fluid continuity, Bernoulli's energy equations, water column momentum, and electro-mechanical energy conversion. Operationally, water is delivered through the penstock under controlled static head, converting potential hydraulic energy into kinetic fluid velocity to drive the turbine runner, generating up to 1 kW of continuous electrical output. System operations focus on monitoring head loss, intake flow rate, runner torque, and rotational speed stabilization under varying resistive loads. Integrating these theoretical parameters into a controlled 1 kW physical model enables real-time evaluation of transient hydraulic behavior, intake gate responsiveness, and power generation dynamics. Ultimately, this operational model bridges fundamental fluid theory with real-world plant operations, offering a scalable platform for academic research, system optimization, and technical capacity building.

Keywords Kainji Hydropower Dam Physical Scale Prototype 1 kW Power Generation Fluid Dynamics Modeling Twin Micro-Turbines Penstock Flow Dynamics Electro-Mechanical Conversion Industry-Academia Collaboration.

CPS-Driven Adaptive Coordination Framework for Heterogeneous Wireless Sensor Networks in Dynamic and Uncertain Environments

Matthew Iyobhebhe — Federal Polytechnic Nasarawa, Nigeria

Matthew Iyobhebhe — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Abdoulie Momodou. S. Tekanyi — Ahmadu Bello University, Zaria. Nigeria, Faculty Of Engineering, Department Of Electronics And Telecommunications Engineering

Athanisius Terlumun Utev — Ahmadu Bello University, Zaria. Nigeria, Faculty Of Engineering, Department Of Electronics And Telecommunications Engineering

Fatima Ashafa — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Asebakeoghene. J. Khama — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Botson Ishaya Chollom — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Umar Salisu Lawal — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

This review manuscript introduces a cyber-physical system (CPS)-driven adaptive management structure for heterogeneous wireless sensor networks (HWSNs) functioning in dynamic and uncertain environments. The increasing heterogeneity of sensing nodes, resource limited, and unpredictable environmental dynamics create significant limitations to reliable and efficient management. Prior techniques often fail to offer real-time dynamic configurability and reliable uncertainty handling. To address these challenges, the developed scheme combines cyber-physical system principles, distributed intelligence, and context-aware decision-making to allow autonomous management among heterogeneous sensor nodes. The framework exploits continuous feedback loops, adaptive control mechanisms, and real-time data analytics to improve network responsiveness and robustness. Additionally, it maintains scalable and energy-efficient implementation across various application scenarios, such as industrial monitoring, smart environments, and critical infrastructure systems. This paper further highlights the following areas such as foundation of CPS and heterogeneous wireless sensor networks, adaptive coordination mechanisms, distributed coordination approaches, research and future directions, and so on.

Keywords Adaptive coordination mechanism in HWSNs Distributed coordination approaches Managing dynamics and uncertainty I CPS-driven HWSNs.

DESIGN AND FABRICATION OF A 5 BSPD PILOT-SCALE SEMI-REGENERATIVE CATALYTIC NAPHTHA REFORMING UNIT

Lamido Sani Inuwa — Kaduna Polytechnic

Ibrahim A Mohammed-dabo — Ahmadu Bello University Zaria

Prof. Maina, N. S — Ahmadu Bello University Zaria

Aminu Uba Alhassan — Kaduna Polytechnic

Bashir Aliyu Abba — Kaduna Polytechnic

Catalytic naphtha reforming process is a vital refinery process where low octane naphtha is converted into high octane reformate while concurrently generating hydrogen gas. This research work presents the design, simulation, and fabrication of 5 barrels per stream day (BPSD) pilot-scale semi-regenerative catalytic naphtha reforming process which serves as part of the mini-refinery development process at the Ahmadu Bello University (ABU), Zaria. The design was based on Escravos Heavy Hydrotreated Naphtha serving as feed; with a capacity of 5 barrel/day. Material and Energy balances calculations were performed on the developed process flow diagram before detailed equipment design was done using Mathcad and Aspen Hysys simulation. The designed equipment that constitute the pilot plant are: Surge Drum (D-01), Heat Exchanger (E-01), Phase Separator (D-02), three Fired Heaters (H-01, H-02 & H-03) and three Fixed Bed Reactors (R-01, R-02 & R-03). R-01 (0.02 m3 volume and 805.2 mm height), R-02 (0.03 m3 volume and 923 mm height) and R-03 (0.04 m3 volume and 105.4.2 mm height). The RON and MON of the produced reformate from the locally fabricated reforming unit was evaluated to be 71 and 64 respectively which is significantly lower than commercial catalytic reforming units.

Keywords Catalytic reforming pilot-scale refinery heavy naphtha process design reformate

Desirability-Based Multi-Response Optimization of Flexural Performance in Bamboo and Steel Reinforced Concrete Beams

Chukwu Mbazor — Alex Ekwueme Federal University Ndufu Alike Ikwo, Nigeria

J. M. Kaura

Amana Ocholi

J. Ochepo

This study presents a comparative optimization and predictive modeling of the flexural properties (deflection and failure load) of bamboo and steel reinforced concrete beams at a target grade of 25 MPa. Utilizing the Optimal Custom Design (OCD) in Response Surface Methodology (RSM), the effects of curing age (7 to 28 days) and reinforcement areas (145 to 580 for bamboo; 50.3 to 201.2 for steel) were analyzed. Sequential model sum of squares recommended third-order cubic polynomial models as the most suitable descriptors. Analysis of variance (ANOVA) validated the significance of these cubic models (), indicating a 99.99% confidence level that the model coefficients are nonzero. Residual diagnostics demonstrated that the experimental errors were approximately normally distributed. The fit summaries indicated exceptionally high predictive power: the adjusted values ranged from 0.9984 to 0.9992, with predicted values agreeing within 0.2, and adequate precision ratios well above the threshold of 4 (ranging from 175.18 to 242.13). Multi-response optimization, aimed at minimizing deflection and maximizing failure load, identified optimal configurations. For the bamboo-reinforced concrete beam, the selected optimal parameters were a curing age of 9.588 days and a bamboo area of 580.000, yielding a deflection of 4.692 mm, a flexural failure load of 9.471 kN, and a desirability value of 0.785. For the steel-reinforced beam, the optimal parameters were an age of 9.926 days and a steel area of 201.200, resulting in a deflection of 6.229 mm, a flexural failure load of 13.865 kN, and a desirability value of 0.782. Since the desirability values are extremely close (0.785 vs. 0.782), this study demonstrates that bamboo reinforced concrete beams achieve highly satisfactory flexural performance comparable to steel-reinforced beams, presenting a sustainable alternative.

Keywords Bamboo reinforced concrete Response Surface Methodology (RSM) Optimal Custom Design (OCD) Flexural properties (deflection failure load) Multi-response optimization Desirability function

Energy-Efficient Communication and Routing Strategies in Heterogeneous Wireless Sensor Networks: A Comprehensive Review

Matthew Iyobhebhe — Federal Polytechnic Nasarawa, Nigeria

Matthew Iyobhebhe — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Abdoulie Momodou. S. Tekanyi — Ahmadu Bello University, Zaria. Nigeria, Faculty Of Engineering, Department Of Electronics And Telecommunications Engineering

Athanisius Terlumun Utev — Ahmadu Bello University, Zaria. Nigeria, Faculty Of Engineering, Department Of Electronics And Telecommunications Engineering

Fatima Ashafa — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Asebakeoghene. J. Khama — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Botson Ishaya Chollom — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Umar Salisu Lawal — Federal Polytechnic Nasarawa, Nigeria, School Of Engineering Technology, Department Of Electrical/electronics Engineering Technology T

Heterogeneous Wireless Sensor Networks (HWSNs) have increased a significant attention due to their ability to improve network performance and maximize network operational lifetime through the combination of sensor nodes with diverse capabilities. However, the occurrence of node heterogeneity presents new challenges in designing energy-efficient communication and routing mechanisms, predominantly under stringent energy limitations. This review introduces a comprehensive scrutiny of existing communication and routing strategies in HWSNs, with a primary focus on energy efficiency and sustainability. The study systematically scrutinizes fundamental HWSN concepts, energy consumption models, communication paradigms, and routing protocols, including flat and hierarchical approaches. Furthermore, recent improvements in energy harvesting, harvesting-aware routing, and hybrid energy storage systems are considered key enablers of sustainable network operation. By combining conventional and emerging techniques, this review identifies critical research challenges and future directions, offering valuable insights for researchers and system designers toward the development of scalable, adaptive, and energy-efficient HWSN solutions.

Keywords Communication strategies Cross-layer communication approaches Energy harvesting in HWSNs Energy-efficient in HWSNs Energy consumption models in HWSNs heterogeneity in HWSNs Routing strategies in HWSNs

Evolution, Prospects, and Future Directions of Nigerian Currency Image Analysis: A Decadal Review.

Isaac Yusuf — University Of Ilorin

Isaac Omeiza — University Of Ilorin

The counterfeit Nigerian banknote (Naira) is still an ongoing challenge; the development of automated image analysis of the Nigerian banknote has been undertaken. This study is a Literature Review spanning 2016-2026 to map the past, present, and future trends of Nigerian currency image analysis. From 150 initial bibliographic entries in the journal, 17 methodologically sound articles were completely published and appraised. The evolution from the review to the report is emphasized, encompassing traditional image processing and conventional machine learning methods, such as color histograms, HOG, etc., as well as ensemble and deep learning architectures (CNN, LSTM, RNN), with some level of accuracy; despite these accuracies often being above 99%, reliable real-world deployment remains elusive. Persistent limitations include small proprietary datasets, sensitivity to defective notes, and high computational demands. The new redesign of the CBN currency in 2022 rendered models invalid. The prediction of other series was done using older series. To make a contribution to the existing knowledge, the research proposes six key research directions: The components of a set that includes benchmarks, domain adaptation for redesigns, the use of lightweight edge AI, multimodal sensor fusion, environmental robustness, and inclusive design. The overall aim of the study is to steer researchers and financial institutions in the right direction and on how to create highly reliable banknote authentication systems, going beyond just getting good scores in the test set.

Keywords Nigerian Naira Currency Authentication Computer Vision Pattern Recognition Decadal Review

Feature Selection Using Random Forest Feature Importance for Efficient Network Intrusion Detection on the NSL-KDD Dataset

Shafiu Shuaibu — Ahmadu Bello University Zaria

Basira Yahaya — Ahmadu Bello University Zaria

Abdulfatai Dare Adekale — Ahmadu Bello University Zaria

Aminu Yakubu — Federal University Of Education Zaria

Abstract
Network Intrusion Detection Systems (NIDS) require informative features to distinguish benign from malicious traffic. This study investigates Random Forest feature importance for reducing the dimensionality of NSL-KDD. Using KDDTrain+, an 80:20 stratified split was applied after preprocessing, producing 121 predictive features. The top 30 features selected by Random Forest reduced dimensionality by 75.21%. Evaluated with an optimized Random Forest, the reduced representation achieved 99.83% accuracy, 99.93% precision, 99.70% recall, 99.82% F1-score, and 0.0594% false-positive rate. The results demonstrate that Random Forest can identify a compact and informative feature subset under the stated experimental conditions. However, computational efficiency was not directly measured, and a full 121-feature baseline must be rerun before confirming performance preservation or improvement.

Keywords Network Intrusion Detection System Feature Selection Random Forest Feature Importance NSL-KDD Machine Learning Cybersecurity.

Physicochemical assessment of hospital waste water through clay membrane composite,a case study of general hospital minna

Imoh Nyong — Ahmadu Bello University Zaria

God Fred Abang Ofono — Ahmadu Bello University

Abstract

Hospital wastewater is a complex mixture of chemical, physical, and biological contaminants generated from various healthcare activities, including laboratories, surgical units, pharmacies, and It contains high concentrations of organic matter, nutrients, which pose serious environmental and public health risks when discharged untreated into receiving water bodies. Conventional wastewater treatment systems often fail to achieve complete removal of these. This study investigates the physicochemical characteristics of hospital wastewater and the effectiveness of a clay membrane composite as an adsorption and filtration medium for wastewater treatment.
Representative wastewater samples are collected from selected discharge points within the hospital and analyzed before using standard methods prescribed by the American Public Health Association (APHA). The physicochemical parameters assessed include pH, temperature, electrical conductivity (EC), turbidity, total dissolved solids (TDS), total suspended solids (TSS), dissolved oxygen (DO), biochemical oxygen demand (BOD₅), chemical oxygen demand (COD), nitrate, phosphate, sulphate, chloride, and selected heavy metals such as lead (Pb), cadmium (Cd), chromium (Cr), copper (Cu), zinc (Zn), and iron (Fe). The clay membrane composite is fabricated from selected clay materials and modified with suitable reinforcing materials to enhance its mechanical strength, adsorption capacity and resistance to membrane fouling. The treatment process combines adsorption and membrane filtration, enabling simultaneous removal of suspended particles.

It is anticipated that the clay membrane composite will reduce turbidity, TDS, TSS, BOD₅, COD, heavy metals, and other pollutants while maintaining pH values within acceptable discharge limits. The treated effluent is subsequently compared with the permissible standards established by the World Health Organization (WHO), the Federal Environmental Protection Agency (FEPA), and the National Environmental Standards and Regulations Enforcement Agency (NESREA) to determine its compliance with environmental discharge regulations.

The findings of this study are expected to demonstrate that clay membrane composite technology offers an efficient,environmentally friendly, and sustainable approach for hospital wastewater treatment

Keywords Pharmaceutical contaminant physicochemical assessment clay membrane

STRUCTURAL RELIABILITY ASSESSMENT OF REINFORCED CONCRETE BEAM INCORPORATING GROUNDNUT SHELL ASH FOR TILAPIA CONCRETE INCUBATOR

Joseph Ogugua Eze — Federal University Of Technology, Minna

Aguwa James — Federal University Of Technology, Minna

Engr. Prof. A. Mohammed — Federal University Of Technology, Minna

Engr. Dr. S.f. Oritola — Federal University Of Technology, Minna

Abstract
Structural reliability is the probability of the structure performing its required function adequately for a specific period of time under stated conditions. Reliability analysis on reinforced concrete beam containing Groundnut shell ash as a partial replacement for cement to reduce cost was conducted in this research. The properties of concrete constituents were determined, COREN concrete mix design guidelines were used and the fresh concrete density was 2130Kg/m3. Twenty (20) concrete cubes of 150mm x 150mm x 150mm size were cast, for each percentage replacement of 0, 5, 10, 15 and 20% respectively, making a total of 400 cubes. The samples were cured for ages of 7, 14, 21 and 28 days and the compressive strengths were determined. The average compressive strength of 21.38N/mm2 at 5% replacement for 28 days curing was determined and used for structural design of the beam. The designed beam was subjected to reliability analysis using First Order Reliability Method (FORM). It was observed that the beam designed was safe in bending under Ultimate Limit State of loading, at the span of 2.7m, 300mm depth, 402mm2 area of steel and 7.454kN/m live load with safety index of 3.90091. Sensitivity analysis revealed that safety index is directly proportional to the depth/area of steel but inversely proportional to the span/ live load of the reinforced concrete beam.

Keywords Structural reliability Compressive strength RC Beam Groundnut shell ash

SWOT Analysis of Local Engineering Innovation for Sustainable Industrial Growth in Nigeria: Pathway to SDG Realization

Anas Mahmoud Ibrahim — Ahmadu Bello University, Zaria

Umar Ibrahim Kwami — Federal Polytechnic, Daura

Abdulmajid Aliyu — Ahmadu Bello University, Zaria. Nigeria

Shuaibu Babandi Shuaibu — Ahmadu Bello University, Zaria. Nigeria

This study examines how local engineering innovation can drive sustainable industrial growth and support Nigeria's progress toward the Sustainable Development Goals, using a SWOT analysis framework. Nigeria's urgent need for economic diversification and technological self-reliance motivates the research. While the federal government has prioritized local content through Presidential Executive Order No. 5 and the Nigeria First Policy, engineering innovation remains essential for building economic resilience and creating jobs. However, the nation continues to struggle with weak university-industry linkages, limited commercialization of research, and inadequate infrastructure. Guided by the Triple Helix Model of academia-industry-government collaboration, the study draws on policy documents, industry reports, and academic literature to assess Nigeria's engineering innovation ecosystem. The findings reveal promising strengths: a vibrant entrepreneurial culture, a growing startup ecosystem with over 98 tech hubs, and supportive policy momentum. Ahmadu Bello University, Zaria host to Nigeria's first Huawei ICT Academy Support Centre exemplifies local innovation potential; its students won the Innovation Competition Grand Prize and the Women in Tech Award at the 2026 Huawei ICT Competition Global Finals, competing against 177 teams from 49 countries. Yet significant weaknesses persist. Only about 5% of engineering graduates are considered industry-ready, while brain drain, low patent commercialization, and fragile infrastructure remain pressing concerns. Opportunities exist through NASENI's 3Cs initiative, which has brought 44 products to market and created over 25,000 jobs, alongside the African Continental Free Trade Area. However, threats such as economic instability, insecurity in the North-East and North-West, and reliance on foreign technology cannot be overlooked. The study concludes that stronger partnerships, increased applied research funding, intellectual property reforms, infrastructure upgrades, and education improvements are vital for harnessing local engineering innovation and advancing SDG 1, 8, 9, and 17 in Nigeria.

Keywords SWOT Analysis Local Engineering Innovation Sustainable Industrial Growth SDGs

THE EFFECTS OF CONCENTRATED SOLAR IRRADIANCE ON THE OVERALL PERFORMANCE OF MONOCRYSTALLINE AND POLYCRYSTALLINE SOLAR CELLS

Lukman Lawal — University Of Abuja

Douglas Uke — University Of Abuja

Abdullahi Mohammed Sb — University Of Abuja

Concentrated photovoltaic (CPV) technology offers a promising approach for enhancing solar energy conversion by increasing the irradiance incident on photovoltaic (PV) cells. However, elevated irradiance is accompanied by significant thermal effects that may adversely affect the electrical performance and reliability of silicon solar cells. This study experimentally investigated and compared the effects of concentrated solar irradiance, ranging from 1 to 10 suns, on the performance of monocrystalline and polycrystalline silicon solar cells. The investigation focused on key electrical parameters, including short-circuit current (Isc), open-circuit voltage (Voc), maximum power output (Pmax), conversion efficiency, fill factor (FF), and series resistance, while also examining the influence of temperature under concentrated illumination.
Baseline performance measurements were first obtained under Standard Test Conditions (1 sun, 25°C, AM 1.5). Thereafter, controlled concentration levels were achieved using a solar simulator and the current–voltage (I–V) characteristics were recorded at concentration ratios between 1 and 10 suns. The results showed that (Isc) increased almost linearly with irradiance, whereas voltage (Voc) exhibited a logarithmic increase before approaching saturation at higher concentration levels. Although maximum power initially increased with concentration ratio, conversion efficiency and fill factor declined beyond the optimum operating range due to elevated cell temperatures and increased resistive losses. Monocrystalline solar cells consistently demonstrated higher efficiency, lower thermal sensitivity, and greater resistance to performance degradation than polycrystalline cells. Critical concentration thresholds were identified, beyond which thermal effects outweighed the benefits of increased photocurrent generation.
The findings demonstrate that concentrated irradiance can substantially improve photovoltaic power output when operated within an optimal concentration range and supported by effective thermal management. This study provides valuable experimental insights for the design, optimisation, and deployment of efficient concentrated photovoltaic systems, particularly in regions with high solar insolation.

Keywords Concentrated solar irradiance Monocrystalline solar cells Polycrystalline solar cells Photovoltaic performance Thermal effects.

CFD-Driven Thermal Analysis and Climate-Adaptive Optimization of Lithium-Ion EV Battery Using Different Cooling Media and Statistical Techniques

Abubakar Unguwanrimi Yakubu — College Of Energy Engineering, Zhejiang University, China

Abubakar Unguwanrimi Yakubu — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China College Of Computing, Engineering And Science, Kaduna State University, Kaduna, 800283, Nigeria Longquan Industrial Innovation Research Institute, Longquan, 323700, China Provinci

Fahim Ullah — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China College Of Computing, Engineering And Science, Kaduna State University, Kaduna, 800283, Nigeria Longquan Industrial Innovation Research Institute, Longquan, 323700, China Provinci

Wang Jiongfan — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China College Of Computing, Engineering And Science, Kaduna State University, Kaduna, 800283, Nigeria Longquan Industrial Innovation Research Institute, Longquan, 323700, China Provinci

Shusheng Xiong — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China College Of Computing, Engineering And Science, Kaduna State University, Kaduna, 800283, Nigeria Longquan Industrial Innovation Research Institute, Longquan, 323700, China Provinci

Jiahao Zhao — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China College Of Computing, Engineering And Science, Kaduna State University, Kaduna, 800283, Nigeria Longquan Industrial Innovation Research Institute, Longquan, 323700, China Provinci

Xuanhong Ye — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China College Of Computing, Engineering And Science, Kaduna State University, Kaduna, 800283, Nigeria Longquan Industrial Innovation Research Institute, Longquan, 323700, China Provinci

Graphical abstract

Abstract

Managing the thermal performance of lithium-ion batteries in electric vehicles (EVs) poses significant challenges due to the wide range of climatic conditions. This paper presents a thorough Computational Fluid Dynamics (CFD) analysis to evaluate the thermal behavior and climate-adaptive optimization of a 21-cell 18650 lithium-ion battery pack. We investigated six cooling methods: ethylene glycol (EG) solutions at 20%, 40%, and 60%; mineral oil at flow rates of 0.03 m/s and 0.05 m/s; and forced-air cooling. The results indicated that the 40% EG solution provided the best overall performance, achieving a cooling efficiency of 91.7%, a temperature rise of just 0.70 K, and a pumping power requirement of 29.5 W. While the mineral oil at 0.05 m/s demonstrated the highest heat rejection capacity of 174.88 W, it consumed 3.2 times more pumping Energy compared to the 20% EG solution. Statistical analysis using ANOVA showed that operating temperature (69.7%), coolant concentration (18.3%), and flow rate (9.2%) are the primary factors influencing the performance of the Battery Thermal Management System (BTMS). Based on our findings, we propose a climate-dependent coolant selection strategy: 20% EG for hot climates (above 35°C), 40% EG for moderate climates (between 20°C and 35°C), and 50-60% EG for cold climates (below 0°C). Notably, forced air cooling performed poorly, rejecting 45% less heat than the 40% EG solution. Additionally, regression models with R² values greater than 0.99 provide quantitative design guidelines for BTMS. This research challenges the SAE J1034 recommendation of using 50% EG across all climates and provides a validated framework for the design of climate-adaptive BTMS solutions

Keywords Lithium-ion battery BTMS Ethylene glycol coolant Heat extraction Electric vehicle Climate-adaptive cooling

Development of a Cyclonic Liquid Spray Scrubber for Emission Control

Hamisu Adamu Dandajeh — Ahmadu Bello University

Tasiu Salisu Abubakar — Ahmadu Bello University

This study presents the design, fabrication, and performance evaluation of a cyclonic liquid spray scrubber for controlling exhaust emissions from an internal combustion engine. The scrubber was fabricated from mild steel and equipped with an exhaust gas inlet and outlet. Its performance was evaluated using the exhaust emissions from a four-stroke, single-cylinder gasoline engine. Emission measurements were conducted using a Brain Bee Automotive Gas Analyzer located in the Heat Engine Laboratory, Department of Mechanical Engineering, Ahmadu Bello University, Zaria. The scrubber was connected to the engine exhaust system, and emission levels were measured under identical operating conditions with and without the scrubber. The results showed that the scrubber reduced the concentrations of carbon monoxide (CO), carbon dioxide (CO₂), and unburned hydrocarbons (HC) by 15.6%, 9% and 19% respectively and surprisingly increased excess oxygen (O₂) emissions by approximately 2%. The average equivalence ratio decreased from 0.2595 without the wet scrubber to 0.2250 with the wet scrubber. Although the prototype exhibited demonstrable effectiveness under the test conditions, the study establishes the feasibility of developing a cyclonic liquid spray scrubber for exhaust gas treatment. With further optimization of its design and operating parameters, the system has the potential to reduce emissions from both stationary and mobile combustion sources.

Keywords Emission Control Cyclonic Liquid Scrubber Gas Analyser Exhaust

Investigation of the Physicochemical Properties and Engine Performance Characteristics of Glycine max Biodiesel–Diesel Blends in a Compression Ignition Engine

Hamisu Adamu Dandajeh — Ahmadu Bello University

Yusuf Hafiz — Ahmadu Bello University

This study investigated the performance and emission characteristics of biodiesel blends produced from Glycine max oil in a compression ignition engine. Biodiesel was produced through transesterification using methanol and potassium hydroxide. The produced biodiesel was blended with conventional diesel at 5% (B5), 10% (B10) and 20% (B20), and burnt in a single-cylinder Kirloskar TV1 diesel engine at speeds of 1200rpm and 1400rpm. Physicochemical properties including density, kinematic viscosity, pour point and flash point were determined. Engine performance parameters such as brake power (BP), brake thermal efficiency (BTE), brake mean effective pressure (BMEP), brake torque (BT) and brake specific fuel consumption (BSFC) were also evaluated. The experimental results showed that increasing Glycine-Max content from 0 – 20% increased the flash point from 71 – 79oC and decreased the kinematic viscosity from 3.327 – 3.269 (mm²/s). While Brake Power (BP) increased with engine speed increase regardless of the blends; the Brake Thermal Efficiency (BTE) decreased with increasing proportion of Glycine-max from 5 – 20% irrespective of the blend. There was decreasing trend for exhaust emissions with increasing biodiesel blend proportions from 5% to 10% and 20% for HC, CO and CO₂. Nitrogen oxide (NOx) emissions increased slightly with increasing biodiesel content. The findings indicate that Glycine-max biodiesel have potential as renewable substitutes for petroleum diesel in compression ignition engines.

Keywords Glycine max Diesel Biodiesel Compression Ignition Engine Engine Performance

Technological and Consumer Barriers to Electric Vehicle Adoption in Nigeria: Evidence from Stakeholder Survey

Ayodele Kolade — Ahmadu Bello University Zaria

Dr. Sabur Ajibola Alim — Ahmadu Bello University Zaria

Prof. Mathew. Olatunde. Afolayan — Ahmadu Bello University Zaria

The transition to electric vehicles (EVs) has emerged as a critical strategy for reducing greenhouse gas emissions and promoting sustainable transportation globally. However, the pace of EV adoption in many developing countries, including Nigeria, remains slow because of persistent technological, economic, and infrastructural constraints. This study examines the technological and consumer barriers influencing electric vehicle adoption in Nigeria using evidence obtained from a stakeholder survey. A mixed-methods descriptive research design was adopted, combining quantitative survey data with stakeholder perspectives to provide a comprehensive assessment of adoption challenges. A total of 382 structured questionnaires were administered to vehicle users, automobile technicians, transport operators, policymakers, renewable energy professionals, and automobile industry stakeholders, of which 321 valid responses were analysed, representing an 84% response rate. Descriptive statistics and Chi-square (χ²) analysis were employed to evaluate stakeholder perceptions and test the relationships between key adoption variables. The findings revealed that affordability remains the most significant constraint, with 91.3% of respondents identifying the high purchase cost of electric vehicles as a major barrier. Battery performance and driving range concerns were reported by 85.1% of respondents, indicating that range anxiety continues to discourage prospective users. Furthermore, 76.3% believed that Nigeria lacks adequate technical expertise and maintenance facilities to support widespread EV deployment, while inadequate charging infrastructure was identified as a major concern affecting consumer confidence. Under existing socioeconomic conditions, respondents demonstrated a stronger preference for Hybrid Electric Vehicles (44.7%) than Battery Electric Vehicles (28.1%) or Plug-in Hybrid Electric Vehicles (27.2%), reflecting a cautious approach to vehicle electrification. The study concludes that accelerating EV adoption in Nigeria will require coordinated policy interventions aimed at reducing acquisition costs, expanding charging infrastructure, strengthening technical workforce development, and improving access to consumer financing.

Keywords Electric vehicles Consumer behaviour Technology adoption Range anxiety Charging infrastructure Sustainable transportation Nigeria.

Comparative Evaluation of AASHTO and CBR Flexible Pavement Design Methods Using Laboratory-Derived Soil Parameters

Ahmad Idris — Bayero University

Flexible pavement design plays a critical role in ensuring the durability, safety, and economic viability of road infrastructure. Various pavement design methods have been developed over the years, among which the California Bearing Ratio (CBR) and the American Association of State Highway and Transportation Officials (AASHTO) methods are widely adopted. This study compares the pavement thicknesses and design implications obtained from these two methods using laboratory-derived soil parameters. Two lateritic soil samples classified as non-marginal and marginal subgrade materials were subjected to particle size distribution, Atterberg limits, compaction, and California bearing ratio tests. The results showed that the non-marginal soil possessed a CBR value of 42.79%, while the marginal soil recorded a CBR value of 13.03%. Flexible pavement structures were designed for a traffic volume of 4,200 vehicles per day, 25% heavy vehicles, a 20-year design life, and a traffic growth rate of 4%. The CBR method produced thinner pavement structures compared with the AASHTO method. For the non-marginal soil, the CBR method yielded pavement layers of 113 mm surfacing, 150 mm base, and 150 mm sub-base, whereas the AASHTO method required 130 mm surfacing, 220 mm base, and 250 mm sub-base for the same soil. For the marginal soil, the CBR method produced 100 mm surfacing, 150 mm base, and 200 mm sub-base, while the AASHTO method resulted in 140 mm surfacing, 230 mm base, and 280 mm sub-base. The findings indicate that the AASHTO method provides more conservative and reliable pavement designs due to its incorporation of traffic loading, reliability, serviceability, and subgrade resilience. The study recommends the use of the AASHTO method for heavily trafficked roads and the CBR method for low-volume rural roads.

Keywords Flexible pavement AASHTO CBR pavement thickness ESAL subgrade strength highway engineering

EFFECT OF POLYCARBONATE PLASTIC ON THE MECHANICAL PROPERTIES OF ASPHALT CONCRETE

Kenneth, Ejike Ibedu — Ahmadu Bello University, Zaria

Abdulfatai, Adinoyi Murana — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria.

Mohammed, Ashiru — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria.

Abdulrahman, Nda’abo Alfa — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria.

In Nigeria, plastics are indiscriminately discarded endangering man and the entire ecosystem. There is need for development of alternative ways in combating challenges of plastic waste disposal. These has necessitated its adoption in asphalt concrete production. This study examined the use of polycarbonate plastic waste as an additive and the effect on strength properties of hot mix asphalt. Polycarbonate is a polymeric material. Fourier Transform Infrared analysis on polycarbonate revealed the presence of aromatic, methyl, carbonyls, amine, and alkene. Scanning electron microscopy and Energy dispersive x-ray spectrometry analysis showed that polycarbonate has spongy shape and the predominant elements are silicon, oxygen, carbon, and aluminum. For the experiment, Marshall method was adopted for mix design and testing. Polycarbonate plastic was introduced into the mix by means of dry process from 1-3% (at interval of 0.5%). The bitumen content used was varied from 6 – 7.5% (at intervals of 0.5%). The introduction of polycarbonate plastic improved the Marshall stability by 20% from 4.67 kN (Threshold) to 5.59 kN (Modified) at 2.5% addition of polycarbonate. Although flow did not improve, other volumetric properties recorded an improvement. This study concludes that an optimal dosage of 2.5% polycarbonate plastic will increase the strength of hot mix asphalt and consequently improve the service life of flexible pavement.

Keywords Polycarbonate Plastic Mechanical Properties Asphalt Concrete Waste.

Effect of Soil Lead Contamination on the Growth Characteristics and Phytoremediation Potential of Sunflower (Helianthus annuus L.), Common Dandelion (Taraxacum officinale), and Jatropha (Jatropha curcas L.)

Sumaila Muhammed Shaibu — Ahmadu Bello University Zaria

Aliyu Adamu Dandajeh — Ahmadu Bello University Zaria

Aliyu Ishaq — Ahmadu Bello University Zaria

Alice Ibrahim Onize — Bayero University Kano, Nigeria

Raphael Ejembi — Ahmadu Bello University, Zaria

Conference Abstract — ICESID 2026
Track: Environmental Engineering and Sustainable Development
Paper Type: Empirical Research

Abstract
Lead (Pb) contamination of soil is a persistent environmental problem because Pb is non-biodegradable, can remain in soil for long periods, and may adversely affect soil quality, vegetation, water resources and human health. This study evaluated the effects of Pb contamination on growth characteristics and the phytoremediation potential of sunflower (Helianthus annuus L.), common dandelion (Taraxacum officinale) and Jatropha (Jatropha curcas L.) under controlled pot conditions at the Institute for Agricultural Research, Ahmadu Bello University, Samaru, Zaria. Topsoil (0–20 cm) was collected, prepared and contaminated with Pb under controlled laboratory conditions. Three kilograms of prepared soil were placed in each pot, seedlings were established, soil moisture was maintained at approximately 65% field capacity, and plants were harvested after 60 days. Plant growth, residual soil Pb, Pb accumulation in roots, stems and leaves, and comparative phytoremediation indicators were assessed. Soil and plant samples were digested and analysed using atomic absorption spectrophotometry. Growth observations were summarized descriptively because seedlings within a pot are not independent experimental replicates. Jatropha recorded the lowest residual soil Pb concentration (82 mg/kg), the highest summed tissue Pb concentration (2,308 mg/kg), and the highest calculated soil Pb reduction (90.4%). Dandelion and sunflower showed calculated reductions of 65.6% and 64.5%, respectively. The highest translocation factors were observed for sunflower (1.84) and dandelion (1.82), compared with Jatropha (1.53). The findings indicate species-specific differences in Pb accumulation and partitioning under the tested conditions; however, the observed soil Pb reductions should be interpreted as preliminary because each species × treatment combination was represented by a single pot. Replicated greenhouse and field-scale studies are required to confirm treatment effects and remediation performance.
Keywords: lead contamination; phytoremediation; Jatropha; sunflower; dandelion; soil remediation; translocation factor.

Keywords Lead contamination Phytoremediation Jatropha Bioconcentration factor Translocation factor.

ESTIMATING GROUNDWATER RECHARGE IN THE BIDA BASIN USING INTEGRATED SOIL MOISTURE BALANCE AND HEC-HMS MODELLING, A CASE STUDY OF THE NEW- BUSSA SUB-BASIN

Salihu Mohammed — Federal University Of Technology Minna

Groundwater is the principal source of domestic and agricultural water supply across much of tropical Africa, yet its sustainable management is constrained by a poor understanding of recharge processes. This study estimates groundwater recharge potential for the Bida Basin, north-central Nigeria, using New Bussa (Borgu Local Government Area) as a representative catchment, selected primarily on data-availability grounds; the extent to which its results can be generalised to the wider, climatically and geologically heterogeneous basin is examined critically. Twenty-five years (2000–2025) of rainfall and temperature data from the Nigerian Meteorological Agency were combined with laboratory-derived soil properties, a Python-based Soil Moisture Balance (SMB) model, and the Hydrologic Engineering Center–Hydrologic Modelling System (HEC-HMS) to simulate runoff and recharge. Iterative calibration, adjusting Curve Number (40–85), lag time (100–323 minutes) and imperviousness (10–25%), produced a best-fit Nash–Sutcliffe Efficiency (NSE) of 0.52 and coefficient of determination (R²) of 0.797 at CN = 40, calibrated against SMB-model-derived rather than independently observed streamflow, so that these statistics reflect internal model consistency rather than field-validated predictive skill. Over 2020–2024, mean annual rainfall was 1,199.32 mm, of which 273.96 mm (22.8%) was converted to runoff and only 31.96 mm (2.7%) recharged groundwater; recharge occurred exclusively in the exceptionally wet year 2020 (159.81 mm), a threshold-controlled response generated only once the accumulated root-zone soil-moisture deficit was fully satisfied. Soils were dominantly sandy loam, with moderate bulk density (1.46–1.61 g/cm³) and available water capacity (10.2–12.2%). The results depict a runoff-dominated hydrological regime in which groundwater recharge is episodic, threshold-dependent, and highly sensitive to rainfall intensity and antecedent soil-moisture conditions, with direct implications for groundwater development planning and for the calibration of hydrological models in comparable tropical savannah basins of the Middle Niger region.

Keywords Groundwater Recharge Soil Moisture Balance Model HEC-HMS Bida Basin Nash–Sutcliffe Efficiency New Bussa

Evaluation of Phosphorus Compound Enrichment and Eutrophication Risk of Alau Reservoir, Nigeria

Yunusa Mamza Usman — Department Of Agricultural And Bio-environmental Engineering, Ramat Polytechnic Maiduguri, Nigeria

Al-amin Danladi Bello — 2. Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria, Nigeria

Badruddeen Saulawa Sani — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria, Nigeria

Umar Alfa Abubakar — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria, Nigeria

Bawu Musami — 1. Department Of Agricultural And Bio-environmental Engineering, Ramat Polytechnic Maiduguri, Nigeria

This study evaluated phosphorus fractions enrichment and eutrophication response variables in Alau Reservoir as limited information exists on the contribution of individual phosphorus fractions and their relationship with eutrophication risk. Enrichment of reservoir with phosphorus remains a major cause of eutrophication that can result in higher production of harmful algae, and can also reduce dissolved oxygen. Water samples were taken from two sampling points (SWA1 and SWA2) for six months, including peak dry, rainy and post-rainy seasons. Standard laboratory methods were used to analyse orthophosphate, organic phosphorus, phosphate, total phosphorus, pH, dissolved oxygen, chlorophyll-a and turbidity. Descriptive statistics and principal component analysis were used to determine the distribution patterns of phosphorus and its relationship with eutrophication indicators. The results showed that the phosphorus enrichment was higher in SWA2 than SWA1 with mean orthophosphate of 0.0059 mg/L and 0.0043 mg/L, org

Keywords Chlorophyll a eutrophication phosphorus enrichment water quality

EXPERIMENTAL ASSESSMENT OF SPECTRUM OCCUPANCY AND TVWS AVAILABILITY IN THE UHF TELEVISION BAND (470–694) MHz IN KANO STATE NIGERIA

Yahaya Hamisu Abubakar — University Of Porthacourt

Mathew Ehikhamenle — Center For Information And Telecommunication Engineering, University Of Portharcourt, Nigeria

This study presents the results of a spectrum measurement campaign conducted in Kano State, Nigeria, across the UHF television band spanning 470–694 MHz. The primary objective was to determine the level of spectrum occupancy and the availability of television white spaces (TVWS) to support dynamic spectrum access in cognitive radio systems. An Agilent (Keysight) spectrum analyser was configured to sweep the television band and collect empirical data from selected urban and rural locations. The findings in urban areas showed a bandwidth utilization of 21.4% (48 MHz out of 224 MHz), corresponding to 6 occupied channels out of 28, leaving 78.6% (176MHz) underutilized. In rural areas, the results indicated that the entire measured spectrum 224 MHz (100%) is available and unoccupied. These findings reveal substantial inefficiency in spectrum usage and suggest significant opportunities for opportunistic access through cognitive radio technologies. The measurement results were further compared with findings from both local and international spectrum occupancy studies, which showed a consistent pattern of low utilization and significant TVWS availability across different locations. This agreement with prior studies supports the technical feasibility of deploying TVWS-based systems for broadband connectivity, Internet of Things (IoT) applications, and indoor coverage enhancement.

Keywords Spectrum Measurement Campaign Spectrum Occupancy Television White Spaces Underutilization of spectrum Cognitive Radio.

Household Water Security and Integrated Water Resources Management Gaps in a Rapidly Urbanising Nigerian City: Evidence from Minna, Niger State

Muhammad Ashafa — Federal University Of Technology, Minna

Professor Mohammed Saidu — Fut Minna

Abstract
Nigeria's freshwater crisis presents a stark paradox: a nation endowed with abundant water resources yet crippled by widespread household water insecurity. Drawing on survey data from 384 households across 21 wards in Bosso and Chanchaga Local Government Areas, this paper investigates the multi-dimensional nature of water insecurity at the household level. Our findings reveal that water insecurity manifests not merely as physical scarcity but as a complex interplay of infrastructural failure, economic burden, governance deficits, and gendered labour. Over 70% of households experience regular interruptions, with coping strategies that disproportionately burden women and children. Monthly water expenditures average ₦1,876, with 40% of households reporting moderate to severe cost burden. While 68% of respondents express distrust in public water quality, reliance on private boreholes and vendor-supplied water remains constrained by affordability and reliability. The paper argues for an integrated approach to water governance that moves beyond supply-side interventions to address the socio-economic and institutional dimensions of water insecurity. We propose a framework grounded in community participation, infrastructure modernization, and equitable pricing mechanisms.

Keywords Water insecurity household survey Nigeria urban water governance HWISE framework water affordability

Hydrological Modelling and Time-Series Streamflow Forecasting of the Kiri Watershed Using SWAT and ARIMA Models

Nura Idris Abdullahi — Ahmadu Bello University Zaria. Nigeria

Hamisu Ahmadu Jalo — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria. Nigeria

Babatunde Karode Adeogun — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria. Nigeria

Jamilu Abdullahi — National Agricultural Extension And Research Liaison Service, Ahmadu Bello University Zaria, Nigeria

Aliyu Adamu Dandajeh — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria. Nigeria

Aliyu Ishaq — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria. Nigeria

Reliable streamflow estimation and forecasting are essential for sustainable reservoir operation, irrigation planning, flood mitigation, and sustainable water resources management. This study evaluated the hydrological responses of the Kiri Watershed (41,516.46 ha) in Adamawa State, Nigeria, and projected future annual streamflow trends over a 20-year horizon (2023 - 2042). The Soil and Water Assessment Tool (SWAT) was calibrated (70% of the data) and validated (30% of the data) using hydro-meteorological inputs from 2000 to 2022 and daily observed streamflow records from the Tallum Hydrological Station. Spatial analysis revealed a watershed dominated by shrublands (90.40%) and loamy soils (55.22%), organized into 9 sub-basins and 44 Hydrologic Response Units (HRUs). SWAT demonstrated high predictive accuracy during both calibration (R2 = 0.83, NSE = 0.79, RMSE = 0.64 m3/s, PBIAS = 2.50%) and validation (R2 = 0.82, NSE = 0.73, RMSE = 0.52 m3/s, PBIAS = 7.58%) respectively. Subsequently, a non-seasonal ARIMA (1,0,0) model was fitted to the aggregated annual streamflow time series. Diagnostic testing via the Ljung-Box test (Q = 4.9011, p = 0.2976) confirmed that the residuals behaved as white noise. The 20-year projection indicates a stable long-term mean annual discharge of approximately 4.0 m3, with no significant upward or downward trend. The findings confirm that while average long-term water yield will remain steady, adaptive reservoir management strategies are necessary to mitigate historical inter-annual discharge fluctuations.

Keywords ARIMA Forecasting Hydrological Modelling Streamflow Simulation SWAT Water Resources Management

IoT-Enabled Hybrid Solar–RF Energy Harvesting Framework for Batteryless Agricultural Monitoring Nodes: A Pathway to Sustainable Rural Development in Nigeria

Vera Ijeoma — Federal University Of Technology Owerri

Chinedu Reginald Okpara — Federal University Of Technology Owerri

Daniel Ikenna Akabuike — Federal University Of Technology Owerri

Favour Chidera Oruche — Federal University Of Technology Owerri

Somtoo-chukwu Samuel Utoh — Federal University Of Technology Owerri

Nigeria's agricultural sector employs over a third of the national workforce yet remains largely rain-fed, poorly monitored, and vulnerable to climate variability, post-harvest loss, and inefficient input use. Precision agriculture built on the Internet of Things (IoT) offers a proven route to higher yields and lower waste, but its adoption in rural Nigerian communities is constrained by two structural realities: unreliable grid electricity and the prohibitive cost of maintaining battery-powered sensor networks across dispersed, often inaccessible farmland. This paper proposes and analyzes a hybrid solar-photovoltaic and radio-frequency (RF) energy harvesting framework that powers batteryless, edge-intelligent soil and microclimate sensor nodes for smallholder farms. The framework combines a low-power PV harvesting front end with an ambient RF/backscatter harvesting subsystem to sustain sensing, local inference, and long-range low-power wide-area network (LPWAN) transmission without disposable batteries or grid dependence. A lightweight edge-intelligence layer performs on-node anomaly detection (soil-moisture stress and abnormal microclimate signatures) to minimize radio duty cycling and reduce energy demand. A subsystem-level energy budget, referenced to a stated 3.3 V rail, shows an average node power draw of the order of a few hundred microwatts, and the supercapacitor storage stage is sized with leakage explicitly accounted for. System architecture, energy-budget analysis, and a phased deployment methodology suited to Nigerian rural infrastructure are presented, alongside a discussion of manufacturing localization, cost, spectrum-regulatory compliance, and policy pathways. The framework directly operationalizes the goal of harnessing engineering to drive Nigeria's growth for sustainable development by offering a maintenance-light, indigenously buildable technology that can improve smallholder yields, reduce post-harvest loss, and create local technical employment in sensor assembly, calibration, and network operations.

Keywords energy harvesting batteryless IoT RF backscatter precision agriculture edge intelligence

MODIFICATION OF FORWARD AND REVERSE ELECTRIC MOTOR STARTERS

Ismail Yusuf Adubazi — Kaduna Polytechnic, Kaduna

Abstract
The two major types of Electric Motor Starters that are utilize in Industries are Direct-On-Line Starter and Star/Delta Starter. Direct-On-Line Starter consists of Contactor, Overload Relay and Switches. The Star/Delta Starter consists of three Contactors, one Overload Relay, one Timer Relay and Switches. For 3-Phase Induction Motor changing the direction of the Electric Motor is by interchanging two of the phases. There are operations that requires flexibility in changing the direction of the processes. Hence there is need to provide means of operating the machine to accommodate easy way of changing the direction. The DOL forward and reverse operation is often realized by two Contactors, one Overload Relay and Switches while the Star/Delta Starter involves four Contactors, One Overload Relay, a Timer Relay and Switches. This research work is designed to implement such operations by reducing the numbers of Contactors that are involved.

Keywords Contactors Overload Relay Timer Relay Forward and Reverse.

Smart Self-Healing Materials: A Comprehensive Review of Emerging Technologies and Future Perspectives

Yakubu Usman — Nigerian College Of Aviation Technology, Zaria

Ibrahim Mu’azu — Kaduna Polytechnic, Kaduna

Gaminana Jimoh — Ahmadu Bello University, Zaria

Danjuma Adamu Ismaila — Nigerian College Of Aviation Technology, Zaria

Self-healing materials represent one of the most significant paradigm shifts in modern materials engineering, offering the ability to autonomously detect and repair internal or external damage without human intervention, thereby extending service life, improving safety, and reducing maintenance costs across engineering applications. This review synthesizes recent advances in smart self-healing materials, covering the three principal design philosophies that underpin the field: capsule-based (extrinsic), vascular and intrinsic self-healing systems. It examines the healing agents, encapsulation strategies, and activation mechanisms employed across polymeric composites, cementitious materials and hydrogel-based systems, and evaluates their translation into real-world sectors including aerospace, automotive, construction, biomedicine, and flexible electronics. Particular attention is given to emerging technologies such as microencapsulated healing agents for structural and cement-based composites, dynamic covalent and supramolecular chemistries that enable repeated intrinsic healing, bio-mediated systems such as bacterially induced self-healing concrete and stimuli-responsive hydrogels for tissue engineering, wound care, and drug delivery. The review further considers how data-driven approaches, including machine learning and artificial intelligence, are beginning to accelerate the discovery, formulation optimization, and predictive modelling of healing efficiency. Despite considerable progress, the field remains constrained by challenges of production scalability, healing-agent depletion after repeated cycles, trade-offs between healing efficiency and mechanical performance, high cost, and the absence of standardized testing protocols. This review contributes to the growing body of knowledge by providing a comprehensive synthesis of emerging technologies and identifying research priorities for future development of smart self-healing materials.

Keywords self-healing materials smart materials microencapsulation vascular networks

UNLOCKING ECONOMIC DIVERSITY: THE STRATEGIC ROLE OF THE METALS INDUSTRY

Muhammad Nur Maina — Ramat Polytechnic, Maiduguri, Borno State

Nigeria’s tax regime does not operate in isolation but as an integral component of the nation’s broader industrialization strategy. Tax policy forms a critical pillar of the institutional framework required to stimulate economic diversification. This paper examines the strategic role of the metals industry in unlocking Nigeria’s economic potential beyond oil dependency. It highlights the importance of a coordinated implementation framework, including clear timelines, technical synchronization of personnel, and effective supervision mechanisms. The study argues that proactive policy direction, investment incentives, and robust institutional reforms are essential to position the metals sector as a backbone for manufacturing and a significant contributor to Gross Domestic Product (GDP). Without sustainable domestic production, Nigeria’s industrial aspirations will remain unattainable. The paper concludes by recommending policy, institutional, and technological pathways for transforming the metals industry into a driver of inclusive economic growth.

Keywords Economic diversification Metals industry Industrialization Tax policy Nigeria Manufacturing

cGAN-Augmented Lightweight CNN Architectures with Coordinate Attention for Maize Leaf Disease Recognition

Sani Saleh Saminu — Ahmadu Bello University, Zaria

Musa Idris Shehu — Ahmadu Bello University, Zaria

Yusuf Ibrahim — Ahmadu Bello University, Zaria

Sani Abdulwahab — Ahmadu Bello University, Zaria

Yakubu Abubakar Hassan — Ahmadu Bello University, Zaria

Emejuo Nichodemus Chibueze — Ahmadu Bello University, Zaria

Deep learning-based plant disease recognition achieves strong benchmark results, but data scarcity and class imbalance consistently limit its reliability when deployed on real field imagery. This study comparatively evaluates four Coordinate Attention-enhanced lightweight CNNs, ShuffleNetV2, MobileNetV3-Small, GhostNet, and EfficientNet-B0, trained with Conditional GAN (cGAN) augmentation on the OSFmaize dataset across four disease categories and five data configurations. Generative quality assessment confirmed acceptable synthetic image quality, with best average FID of 198.57 at epoch 700 and best IS of 3.32 at epoch 1,000. In the primary Real + cGAN configuration, MobileNetV3-Small achieved the highest accuracy at 94.06% with 1.11M parameters, 0.061G FLOPs, 5.10ms inference, and 4.43MB storage, representing the best accuracy-efficiency trade-off among all four models. GhostNet recorded 80.07%, attributed directly to shortcut learning caused by training from scratch without pretrained weights, producing a 19.93 percentage point accuracy drop when real data was added to synthetic-only training. Traditional augmentation outperformed cGAN in all combined training scenarios. Ablation confirmed Coordinate Attention contributes up to 12.24 percentage points accuracy gain. These results provide practical guidance for architecture and augmentation selection in resource-constrained maize disease recognition systems.

Keywords Maize leaf disease recognition Conditional GAN Lightweight CNN Coordinate Attention Data augmentation MobileNetV3-Small

Deep Learning Network for Audio-Based Environmental Sound Recognition using YAMNet and Dense Self-Attention Mechanism

Shehu Mohammed Yusuf — Ahmadu Bello University

Kabiru Muhammed Nasiru — Computer Engineering, Ahmadu Bello University, Zaria, Nigeria

Environmental sound recognition has become increasingly important in applications ranging from smart surveillance to health monitoring and intelligent urban systems. Although recent deep learning models have improved the ability to classify complex acoustic events, many of them still struggle with redundant features in audio embeddings or rely on heavy architectures that limit deployment on resource-constrained devices. To address these challenges, we developed a lightweight framework that combines YAMNet’s pre-trained audio embeddings with a simple one-dimensional self-attention mechanism. This design helps the model focus on the most informative parts of each audio segment while avoiding unnecessary computational overhead. The enhanced embeddings are then processed through a compact fully connected network for final classification. Experiments on two benchmark datasets, ESC-10 and BDLib, demonstrate the effectiveness of the proposed approach, achieving test accuracies of 96% and 97%, respectively. The model outperforms an Xception-based transfer learning baseline on ESC-10 by 2.7% while using roughly 45× fewer parameters and provides competitive performance to MobileNetV2 on BDLib with only a fraction of its complexity. These results indicate that applying self-attention directly to pre-trained audio embeddings can significantly improve environmental sound classification and offers a practical solution for real-time acoustic monitoring in embedded or noisy environments.

Keywords Environmental sound classification Neural Networks Self-Attention Mechanism transfer learning

Deep Learning-Based Weapon Recognition in Intelligent Surveillance Systems

Kenneth Okhiria — Nigerian Army University Biu

Joseph Samuel Mshelizah — Nigerian Army University Biu

Saidi Abdulraimi — Non Affiliated

Weapon-related crimes pose significant threats to public safety and security, creating a growing need for intelligent surveillance systems capable of automatically identifying potential threats. Deep learning has demonstrated remarkable success in object recognition and image classification, making it well suited for automated weapon recognition. This study develops and evaluates a transfer learning-based approach for classifying two common weapon categories, AK-47 rifles and knives, using a pre-trained ResNet-50 convolutional neural network. A dataset comprising 2,000 labeled images was collected from Google Images, manually cleaned, preprocessed, and divided into training and validation sets using an 80:20 ratio. The pre-trained ResNet-50 model was fine-tuned on the ImageNet feature representations and trained for 50 epochs. Model performance was evaluated using precision, recall, F1-score, and overall accuracy. Experimental results demonstrated high classification performance on the validation dataset, with the AK-47 class achieving a precision of 0.99, recall of 1.00, and F1-score of 0.99, while the knife class achieved precision, recall, and F1-score values of 0.99, resulting in an overall classification accuracy of 0.99. Additional inference on previously unseen weapon images produced accurate predictions with consistently high confidence scores, suggesting good predictive consistency beyond the training and validation data. These findings demonstrate the effectiveness of the proposed approach for automated weapon classification and highlight its potential for intelligent surveillance and public safety applications.

Keywords Weapon Classification Deep Learning Transfer Learning ResNet-50 Surveillance Systems

Design and Implementation of an AI-Based Smart Medication Identification, Automated Dispensing, Timed Reminder, and Monitoring Dashboard System

Oluwafemi Lawal — Ahmadu Bello University, Zaria

Oreofe Ajayi — Ahmadu Bello University, Zaria

David Ejila Oiwona — Ahmadu Bello University, Zaria

Abdulhafeez Tahir Adamu — Ahmadu Bello University, Zaria

Mohammed Abubakar — Ahmadu Bello University, Zaria

Muhammad U. Nafiu — Ahmadu Bello University, Zaria

Abstract

Medication errors and poor medication adherence remain important patient-safety challenges, particularly in healthcare environments where medication identification, dispensing, scheduling, and monitoring depend heavily on manual processes. This paper presents the design and implementation of an AI-Based Smart Medication Identification, Automated Dispensing, Timed Reminder, and Monitoring Dashboard System developed as a functional prototype for improving medication management. The system is built around a Raspberry Pi 4 Model B, which serves as the central processing and control platform. The medication identification component employs an EfficientNet-B4 image classification model trained to recognize 112 medication classes. The dataset comprised 4,480 images, consisting of 3,136 training images, 672 validation images, and 672 held-out test images. On the independent test set, the trained model achieved a classification accuracy of 99.85%. The embedded dispensing subsystem uses stepper motors and motor-driver interfaces to control medication compartments, while infrared sensors provide feedback on medication passage during dispensing. A DS3231 real-time clock provides hardware-based timing for scheduled medication events and reminder operation. The system also incorporates a camera-based evidence subsystem for recording dispensing events, a TFT interface for local interaction, and a Flask-based backend with an SQLite database for managing medication records, schedules, stock information, dispensing events, and evidence records. An Android mobile application provides remote access to medication information, system status, evidence records, settings, and selected hardware diagnostic functions. System-level testing demonstrated successful operation of the backend, hardware interfaces, alarm subsystem, scheduling workflow, dispensing controls, camera evidence service, TFT interface, and mobile application. However, the evaluation represents a functional engineering prototype rather than a clinically validated medication administration system, and further testing involving larger datasets, repeated dispensing trials, long-duration operation, and real users is required. The project demonstrates the feasibility of combining artificial intelligence, embedded automation, and remote monitoring into a low-cost medication-management platform with potential applications in Nigerian healthcare and home-care environments.

Keywords Artificial Intelligence Medication Identification Medication Dispensing EfficientNet-B4 Raspberry Pi Medication Adherence Embedded Systems Healthcare Automation.

Design And Performance Evaluation of An Intelligent UAV-Based Vision System For Automated Power Transmission Line Component Inspection Using YOLOv8s

Asmau Sanusi Gumbi — Ahmadu Bello University Zaria

Sani Salisu — Ahmadu Bello University Zaria

Adamu Saidu Abubakar — Ahmadu Bello University Zaria

Mohammed Dikko Amustapha — Department Of Electronics And Telecommunications Engineering

Sulaiman Garba — Nigerian Communication Communications, Abuja

Abstract
Reliable inspection of power transmission infrastructure is essential for maintaining power system stability and preventing equipment failures. However, conventional inspection methods are labour-intensive, time-consuming, and expose personnel to operational hazards, creating the need for intelligent automated inspection systems. This paper presents the design, implementation, and performance evaluation of an intelligent UAV-based vision system that integrates UAV-acquired imagery with the YOLOv8s object detection model for automated inspection of power transmission line components. Transfer learning was employed to adapt the detector using the publicly available InSPLAD dataset, which contains 18 annotated transmission line component classes, comprising 7,946 training images and 2,753 validation images. System performance was evaluated using Precision, Recall, mean Average Precision at an IoU threshold of 0.50 (mAP@50), and mean Average Precision across IoU thresholds from 0.50 to 0.95 (mAP@50–95). The proposed system achieved a Precision of 89.5%, Recall of 86.2%, mAP@50 of 88.4%, and mAP@50–95 of 72.1%, indicating robust detection accuracy and localization capability across diverse transmission line components. These results demonstrate that integrating UAV technology with deep learning-based vision systems provides an effective solution for automated transmission line inspection, supporting safer, faster, and more reliable monitoring of modern power transmission infrastructure.

Keywords Intelligent vision system UAV inspection YOLOv8s power transmission lines object detection InSPLAD dataset

DESIGN AND PROOF-OF-CONCEPT EVALUATION OF A GROWTH-STAGE-ORIENTED ESP32-BASED SMART DRIP IRRIGATION SYSTEM FOR BELL PEPPER PRODUCTION IN SEMI-ARID NIGERIA

Bwala Sarah — Ahmadu Bello University, Zaria

Dr. U.d Idris — Department Of Agricultural And Environmental Engineering, Ahmadu Bello University, Zaria

Garba H.m — Department Of Postharvest Technology, Federal College Of Agricultural Produce Technology, Kano

Water availability and changing crop water demand make irrigation management difficult in semi-arid production systems. This paper presents the design and proof-of-concept evaluation of a growth-stage-oriented smart drip irrigation prototype for bell pepper. The system uses an ESP32 controller with a capacitive soil-moisture sensor, DHT22 temperature and humidity sensor, DS18B20 soil-temperature sensor, YF-S201 flow sensor, DS3231 real-time clock, relay-controlled pump, drip line, LCD, and manual controls. We defined a growth-stage framework using days after transplanting (DAT), provisional soil-moisture thresholds, and maximum irrigation durations; these settings are engineering assumptions rather than validated agronomic optima. We established five four-week-old bell pepper seedlings in one prototype box and monitored them over 19 morning/evening observation periods. The recorded dataset contained air temperature, soil temperature, relative humidity, soil moisture, and independently measured irrigation volume. Across the 19 periods, total recorded irrigation was 6.35 L, comprising 2.65 L in the morning and 3.70 L in the evening. Mean air temperature was 24.48 °C in the morning and 32.37 °C in the evening, while mean soil moisture was 86.79% and 65.26%, respectively. Three response-time observations of 0.488, 0.406, and 0.590 s gave a mean of 0.495 ± 0.092 s. The observations demonstrate that the prototype can acquire environmental data and deliver measured irrigation under live-crop conditions, but they do not establish seasonal water-use efficiency or water-saving performance. Further replicated calibration, controlled comparison, full-cycle crop monitoring, and field testing are required.

Keywords smart irrigation drip irrigation ESP32 bell pepper growth-stage irrigation water management

DESIGN AND SIMULATION OF ARTIFICIAL INTELLIGENCE-BASED ADAPTIVE PROTECTION SCHEME FOR NIGERIA'S POWER GRIDS USING BIG DATA ANALYTICS

Tolulope Adelugba — University Of Abuja

Eronu Emmanuel — University Of Abuja

Ogunjuyigbe Jacob Kehinde — University Of Abuja

Conventional distance relay schemes often fail to detect high impedance faults on Nigeria’s 330 kV transmission network, contributing to grid instability and unreliable supply. This study proposes an adaptive deep neural network protection system for the Shiroro–Jebba–Oshogbo corridor, leveraging Big Data Analytics and convolutional neural networks (CNN) to overcome impedance based limitations. Using MATLAB/Simulink, the corridor was modeled with validated parameters, and 1,000 fault scenarios across seven fault types and six locations were simulated, varying resistance from 0.01Ω to 500Ω. This produced 5.6 million measurement points. A CNN with four convolutional blocks and 1.39 million trainable parameters was implemented in TensorFlow/Keras, trained on 700 scenarios, validated on 150, and tested on 150. The model achieved 98.67% accuracy on unseen data, with an inference time of 100.56 ms. Performance was perfect (100%) for resistances up to 100Ω and remained strong (92%) at 500Ω, where conventional relays fail. Comparative analysis showed CNN sensitivity of 100% versus 21.48% for distance relays, a 78.52-point improvement, as confirmed by McNemar’s test (p

Keywords Adaptive protection Big Data Analytics Convolutional Neural Networks distance relay high impedance faults Nigerian power grid transmission line protection

DEVELOPMENT OF A YOLO – BASED OBJECT DETECTION MODEL FOR ESAL COMPUTATION IN VEHICLE TRAFFIC COUNT

Abdulhameed Umar Abubakar — Modibbo Adama University, Yola

Ayodeji Abioye — The Open University, Milton Keynes

Moses Akujobi — Modibbo Adama University

Raphael J. Mailabari — Modibbo Adama University, Yola

Maimuna S. Tabra — Gombe State University

Vehicle traffic count is an integral part of traffic measurement and forms the basis of road design. In developing countries like Nigeria, this involves manual counting of vehicles passing through a designated region of interest (ROI) to estimate the Equivalent Single Axle Load (ESAL). In this study, a YOLOv11-based model was used to detect, recognize, count and classify vehicles for the computation of ESAL. Bag of Tricks (BoT) for SORT, a multi-object tracking (MOT) algorithm, was used for tracking, while ROI-based counting was done in a rectangular region of interest. Vehicles detected were fine-tuned with COCO-pretrained weights and evaluated using a 10-minute test video based on a manual counting baseline. The vehicle count was connected to transportation engineering quantities using standardized flow rate and ESAL measurements. Results of the flow rate analysis indicated that both the tuned and default models report similar total flow rate with the baseline, an indication of object (vehicle) detection. However, there were instances of misclassification of the detected vehicle class. ESAL rate computed for the baseline, tuned, and default models showed an inflation of the default model compared to the baseline due to exaggerated truck counts as a result of misclassification. Whereas the tuned model produces a much smaller conservative estimates, thus partially correcting the class recognition. This is a reflection that ESAL is sensitive to heavy vehicle misclassification, which may lead to pavement loading estimates distortion. Future research should examine the impact of the recently released YOLOv26 on the dataset.

Keywords Traffic flow measurement ESAL YOLO Object detection ROI-based counting

DEVELOPMENT OF AN AUTOMATIC COIL WINDING MACHINE

Abubakar Umar — Ahmadu Bello University, Zaria

This article presents the development of an automatic coil winding machine. The proposed technique provides an efficient solution for a wide range of coiling operations in electrical and electronic manufacturing. The system significantly reduces the physical effort and time consumption associated with manually operated winding machines, thereby eliminating common inconveniences faced by coil winders. The primary objective of the machine is to overcome the inherent challenges of manual winding, such as overwinding, coil misalignment, non-uniform winding patterns, inaccuracy in turn counts, and slow operational speed. In addition, the proposed system aims to minimize manufacturing costs, reduce technician workload, and enhance overall productivity in small-scale and educational production environments. The coil winding or rewinding machine is commonly employed to transfer wire from a spool onto a former (winding fixture) and accurately attach it to the winding head. The developed system is also suitable for instructional purposes, enabling students to practically learn the winding of small transformers, electric motors, and relay coils. This article incorporates Arduino-based programming to automate the winding process and ensure precise control of operational parameters. The main components of the automatic coil winding machine include a liquid crystal display (LCD) for displaying the number of turns, push buttons for user input, an infrared (IR) sensor for turn counting, and a DC motor to drive the winding mechanism. Experiment was conducted, and the results showed that the developed automatic coil winding machine performed better of about 95% in terms of high precision and accuracy of achieving the desired number of coils turns. The system therefore proves to be reliable, efficient, and suitable for both educational and small-scale industrial applications.

Keywords DC Motor Liquid Crytal Display (LCD) Infrared Sensor Arduino Uno Motor Speed Controller

DEVELOPMENT OF AN IOT BASED SMART SYSTEM FOR COLD SUPPLY CHAIN STORAGE AND TRANSPORTATION

Abubakar Umar — Ahmadu Bello University, Zaria

Cold supply chains have gained increased importance due to the demand pressures which arose from higher consumption levels. However, in order to meet the standards and customer requirements regarding the storage and transportation of cold supply chain products, especially foods and pharmaceutical products, it is important to monitor these conditions throughout the process. Hence, this article presents the development of an IoT based smart system which is aimed at optimizing the cold supply chain operations. The system ensured product quality and safety by systematically monitoring critical environmental parameters such as temperature and humidity. Through the integration of NodeMCU ESP8266 microcontroller, DHT11 sensor and 16x2 LCD. The developed system was designed and implemented locally, while it effectively collects, process and displayed real-time data. An application called cold guard was developed to facilitates remote monitoring and control, thereby enhancing system accessibility and responsiveness. By addressing critical challenges posed by the cold supply chain, which includes product spoilage and supply chain visibility, the technique seeks to develop a robust and scalable solution. The effective implementation of the proposed system is expected to increase the supply chain efficiency, minimize product losses and strengthen consumer trust in the integrity of cold chain products. The results obtained when the data was collected showed satisfactory performance as compared to other existing literature.

Keywords Storage System Supply Chain IoT NodeMCU ESP8266 microcontroller DHT11 Sensor.

Extended Kalman Filter-Based State Estimation for Real-Time Glucose-Insulin Digital Twins in Type 1 Diabetes

Sani Saminu — University Of Ilorin

Idris Oladele Muniru — Biomedical Engineering Department, University Of Ilorin, Ilorin, Nigeria

Suleiman Abimbola Yahaya — Biomedical Engineering Department, University Of Ilorin, Ilorin, Nigeria

Muhammad Kabir Abdulkadir — Department Of Radiography, University Of Ilorin, Ilorin, Nigeria

Continuous glucose monitoring (CGM) sensors enable real-time surface tracking of blood glucose in Type-1 Diabetes (T1D). However, raw subcutaneous CGM readings suffer from additive measurement noise (σ ≈ 15 mg/dL) and physiological lags, whilst critical internal physiological dynamics—specifically interstitial remote insulin action X(t) and plasma insulin concentration I(t)—remain unmeasurable from surface sensing alone. Furthermore, existing healthcare digital twin implementations suffer from a fundamental gap: the Lack of Formal State Estimation, treating twin models as offline predictors without continuous non-linear state updating or uncertainty quantification. This paper presents an Extended Kalman Filter (EKF) state estimation framework designed for glucose-insulin digital twins. Integrating a physical patient model with a non-linear Bergman Minimal Model virtual surrogate, the EKF linearises continuous system dynamics at each time step via discretised Jacobians and maintains numerical covariance symmetry using a Joseph-form update. Evaluated on an 8- hour trial with three unannounced meal disturbances (50g, 70g, and 60g CHO), the EKF reduces glucose estimation root-mean- square error (RMSE) by 52.0% compared with raw CGM signals (6.65 mg/dL vs 13.84 mg/dL) while accurately reconstructing unobserved states ˆX(t) and ˆI(t) with dynamic ±2σ confidence bounds. Robustness benchmarks under 60% model parameter mismatch demonstrate stable state tracking (RMSE 6.69 mg/dL). Mean step execution latency is 245.3 ms (< 0.08% of the 5- minute sampling budget), confirming edge deployment suitability for real-time physiological digital twins.

Keywords blood glucose Type-1 diabetes digital twin extended kalman filter glucose-insulin

Fault Classification in Transmission Line using ANN, Extreme Gradient Boosting and Random Forest Machine Learning Models.

Joshua Alberah — Ahmadu Bello University, Zaria.

G.a. Olarinoye — Ahmadu Bello University, Zaria.

A.s. Abubakar — Ahmadu Bello University, Zaria.

A.b Kunya — Ahmadu Bello University, Zaria.

S.h Sulaiman — Ahmadu Bello University, Zaria.

The rapid advancement of power systems and smart grids necessitates the development of robust fault classification techniques to ensure reliable and resilient electrical power delivery. This paper presents a machine learning-based methodologies for fault classification in power transmission lines. The study explores extreme gradient boosting (XGBoost), random forest (RF) and Artificial Neural Network (ANN) machine learning models for the fault classification. Aimed to classify no-fault, single line-ground fault, double line fault, double line-ground fault, three-line fault and three line-ground faults. The machine learning models were evaluated based on key performance metrics such as accuracy, precision, recall, and F1-score. The scheme was validated on Kaggle pre-fault and post-fault line voltage and current signals. The XGBoost perform with an accuracy of 84.47 %, precision of 84.40 %, recall of 82.30 % and F1-score of 81.79 %, the RF with an accuracy of 83.93 %, precision of 84.68 %, recall of 83.93 % and F1-score of 84.13 % and the ANN with an accuracy of 86.35%, precision of 90.73 %, recall of 83.81 % and F1-score of 82.54 % respectively. This study represents a significant contribution to advancing machine learning techniques in improving the efficiency and efficacy of fault management in high-voltage transmission lines.

Keywords ANN Classification Extreme Gradient Boosting Machine Learning Random Forest.

Fuzzy-Intelligent PID Control for Anode Pressure Regulation in PEMFC Systems: A Hardware-in-the-Loop Validation Study

Abubakar Unguwanrimi Yakubu — College Of Energy Engineering, Zhejiang University, China

Abubakar Unguwanrimi Yakubu — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China College Of Computing, Engineering And Science, Kaduna State University, Kaduna, 800283, Nigeria Longquan Industrial Innovation Research Institute, Longquan, 323700, China Provinci

Jiahao Zhao — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China

Xuanhong Ye — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China

Fahim Ullah — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China

Shusheng Xiong — College Of Energy Engineering, Zhejiang University, Hangzhou, 310027, China Longquan Industrial Innovation Research Institute, Longquan, 323700, China Provincial Key Laboratory Of New Energy Vehicles Thermal Management, Longquan, 323700, China

Proton Exchange Membrane Fuel Cells (PEMFCs) require precise anode pressure regulation to ensure optimal performance, prevent fuel starvation, and extend stack durability. However, conventional PID controllers have inherent limitations in handling rapid load changes, purge-valve disturbances, and system nonlinearities. This paper presents a novel Fuzzy-Intelligent PID (Fuzzy-iPID) controller, integrated with an Extended State Observer (ESO), for adaptive disturbance rejection in PEMFC hydrogen supply systems. We developed a comprehensive control-oriented dynamic model that incorporates electrochemical, thermodynamic, and fluid-dynamic behaviors. We validated this model against experimental data, achieving voltage prediction errors below 3% and pressure prediction errors below 5%. The proposed controller was rigorously evaluated through Hardware-in-the-Loop (HIL) testing, which simulated transient load variations and periodic purge operations. The results demonstrated that the Fuzzy-iPID controller achieved a 94% reduction in mean pressure overshoot (6.25 Pa compared to 103.5 Pa for the PID controller). It also reduced response time by 80% (0.09 seconds compared to 0.46 seconds) and showed significantly lower performance variability. Furthermore, the controller minimized voltage fluctuations and improved electrochemical stability, mitigating degradation mechanisms such as membrane stress, flooding, and nitrogen accumulation. This validated control architecture bridges the gap between theoretical control design and practical PEMFC implementation, establishing a foundation for real-time digital twin integration and predictive maintenance

Keywords PEMFC anode pressure control fuzzy logic intelligent PID extended state observer hardware-in-the-loop

INTEGRATION OF CNN-LSTM SHORT-TERM LOAD FORECASTING INTO DISTRIBUTION NETWORK OPERATIONAL PLANNING

Dorcas A.a Gomna — Federal University Of Technology Minna

James Garba Ambafi — Federal University Of Technology Minna

Lanre Joseph Olatomiwa — Federal University Of Technology Minna

Jibril Abdullahi Bala — Federal University Of Technology Minna

Integrating short-term load forecasts into distribution network operational planning is an emerging research direction that promises to improve network efficiency and reliability. However, the practical value of forecast-driven operation depends critically on forecast quality. This study investigates a hybrid Convolutional Neural Network–Long Short-Term Memory (CNN-LSTM) model, trained on 5,025 hourly observations from Abuja Electricity Distribution Company (AEDC), Minna, to ascertain if it can improve feeder reconfiguration decisions on the IEEE 33-bus radial distribution system. The CNN-LSTM model was implemented in MATLAB R2024b and compared against ARIMA and persistence baselines using Mean Absolute Error (MAE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), and the coefficient of determination (R²). The CNN-LSTM achieved an RMSE of 159.48 MW, MAE of 54.42 MW, MAPE of 31.38%, and R² of 0.0238 performance that is not statistically better than ARIMA (Diebold-Mariano p=0.3606) or persistence (p=0.1036). When the CNN-LSTM forecasts were used to guide feeder reconfiguration and the chosen topology was evaluated against actual realised load, the forecast-driven approach produced a 33.34% reduction in active power loss. However, this was outperformed by reconfiguration with no forecast (34.39% loss reduction), indicating that the poor forecast quality introduced operational decisions that were worse than doing nothing. The results demonstrate that forecast-driven operation is not universally beneficial and is only justified after the forecasting model achieves statistically significant superiority over strong baselines. The study contributes a cautionary framework that establishes a minimum forecast quality threshold for operational planning in distribution networks

Keywords CNN-LSTM short-term load forecasting distribution network operational planning feeder reconfiguration.

Metaheuristic Optimization Strategies for Synthetic Inertia and Load Frequency Control in Islanded Microgrids: A Comprehensive Review

Nurudeen Abdulazeez — Ahmadu Bello University Zaria- Kaduna

Abdullahi Bala Kunya — Department Of Electrical And Computer Engineering, Kampala International University, Kampala, Uganda

Abdulkarim Abubakar — Department Of Electrical And Computer Engineering, Kampala International University, Kampala, Uganda

Adamu Saidu Abubakar — 4department Of Electrical Engineering, Faculty Of Engineering, Ahmadu Bello University, Zaria-nigeria

Islanded microgrids (IMGs) featuring high penetration levels of inverter-based renewable energy sources (RESs) suffer from severe dynamic instability, rapid rate of change of frequency (RoCoF), and deep frequency nadirs due to the low or zero physical inertia of power electronic interfaces. To compensate for lost rotational kinetic energy, Synthetic Inertia Control (SIC) and dynamic Load Frequency Control (LFC) have emerged as essential stabilization mechanisms. However, conventional linear controllers (e.g., PI/PID) underperform under stochastic load variations, intermittent wind/solar generation, nonlinear governor deadbands, and variable time delays. Over the past decade, metaheuristic optimization algorithms (MOAs) spanning swarm intelligence, evolutionary computation, physics-based, and human-inspired paradigms have transformed control parameter tuning, objective function formulation, and hybrid controller design in IMGs. This paper provides a rigorous, state-of-the-art review of metaheuristic optimization strategies applied to joint or standalone SIC and LFC schemes in standalone microgrids. We classify contemporary control topologies, examine classical and high-order objective metrics (ITAE, ITSE, multi-objective trade-offs), and critically evaluate metaheuristic paradigms ranging from foundational algorithms (PSO, GA, GWO) to modern hybrid and adaptive variants (e.g., Starfish Optimization Algorithm, Wild Horse Optimization). Furthermore, we detail the integration of physical energy storage systems (BESS, FESS) and demand-side assets like Electric Vehicles (EVs) for frequency support. Finally, key open research challenges, including real-time computational overhead, hardware-in-the-loop (HIL) validation, cyber-physical security, and multi-objective Pareto optimization are systematically analyzed to delineate future research directions.

Keywords Islanded Microgrid Synthetic Inertia Control (SIC) Load Frequency Control (LFC) Metaheuristic Optimization Rate of Change of Frequency (RoCoF)

Mission-Aware Optimization of Deployable Renewable Energy Systems for Critical Rural Services in Nigeria: A Reconfiguration Framework

Waliu Musa — Federal University Of Agriculture, Abeokuta

Taiwo Emmanuel Okharedia — Department Of Electrical And Electronic Engineering, Atlantic International University, Hawaii, Usa

Muhammed Ibrahim — Department Of Electrical/electronic Engineering, Federal University Of Petroleum Resources, Effurun, Delta State, Nigeria

Aneke Nnamere Ezekiel — State University Of Medical And Applied Sciences, Igbo-eno Orba, Enugu State, Nigeria

Isaac Adekanye — Operations Manager, Detrio Consult Limited, Lagos, Nigeria

Oluwaseun Adebisi — Department Of Electrical/electronic Engineering, Federal University Of Agriculture, Abeokuta, Ogun State, Nigeria

Umar Abubakar Saleh — Department Of Electrical And Electronic Engineering, Federal University Lokoja, Kogi State, Nigeria

Rural communities in Nigeria often require electricity for different critical services at different times, including agricultural activities, healthcare, and emergency response. Conventional rural renewable-energy systems are generally fixed-purpose installations, while existing mobile energy-storage research largely focuses on restoration, routing, sizing, and pre-positioning. This paper proposes a Mission-Aware Reconfigurable Energy Hub (MAREH), a deployable photovoltaic–battery energy storage system that retains a common energy backbone while reconfiguring its load priorities according to the active rural mission. The framework integrates PV generation, battery storage, supervisory energy management, mission-dependent critical-load prioritization, and deployment-specific electrical safety verification. A two-stage approach is used: the first stage sizes the PV-battery configuration under an ε-constraint formulation minimizing lifecycle cost subject to explicit service-reliability constraints, and the second stage evaluates the sized system, without further optimization, under three missions - agricultural support, healthcare, and emergency response - using scenario-based deterministic simulation. Four scenarios compare fixed-purpose, conventional deployable, and mission-aware configurations using energy not served, critical energy-service coverage (CESC), renewable fraction, battery state of charge, and system cost. Preliminary results indicate the mission-aware configuration achieves approximately 99% or greater critical-service coverage across the three missions using a 7-kWp PV array and 22-kWh battery, an 8.3% reduction in nominal storage capacity relative to the conventional deployable benchmark. This reduction is accompanied by a small decrease in worst-case coverage (approximately 0.65 percentage points), reflecting a deliberate trade-off in which lower-priority loads are curtailed to protect critical services under scarcity, rather than a uniform improvement. The framework demonstrates that reconfigurability can serve as an additional energy-system resource, letting one deployable renewable-energy asset support changing rural priorities without separate dedicated systems at a quantifiable and disclosed reliability cost.

Keywords mission-aware energy hub mobile microgrid PV–BESS rural electrification reconfigurable energy system critical services Nigeria

POWER TRANSFORMER INCIPIENT FAULT PREDICTION USING DISSOLVED GAS ANALYSIS AND ARTIFICIAL BEE COLONY OPTIMIZED RANDOM FOREST MODEL

Abdulkadir Itopa Isa — Abubakar Tafawa Balewa University Bauchi

Yau Haruna Shuaibu — Abubakar Tafawa Balewa University Bauchi

Abdullahi Amoo — Abubakar Tafawa Balewa University Bauchi

Ganiyu Ayinde Bakare — Abubakar Tafawa Balewa University Bauchi

Mustapha Musa — University Of Maidugiuri

Abstract. Power transformers are critical assets in electric power systems, and their reliable operation is essential for preventing catastrophic failures and power outages. Continuous condition monitoring is therefore necessary for the early detection of incipient faults. Dissolved Gas Analysis is widely adopted as a diagnostic technique but its effectiveness can be constrained by variability in diagnostic results. Conventional methods have limited capability to provide reliable fault diagnosis and often produce ambiguous or “no decision” outcomes when gas ratios fall outside standard ranges or overlap across multiple fault zones. Similarly, standalone artificial intelligence and machine learning algorithms may have limited generalization capability and perform poorly under new or varying data conditions due to non-optimal hyperparameters. Their performance is also highly dependent on the quality and quantity of training data, making them susceptible to noise, missing values, class imbalance, overfitting, and underfitting. To address these limitations, this study proposes a data-driven transformer fault diagnosis framework based on Artificial Bee Colony (ABC) hyperparameter optimization. The proposed framework employs ABC to optimize the hyperparameters of Support Vector Machine and Random Forest classifiers, while Deep Neural Network is included as a benchmark model. The DGA dataset consists of 589 samples with five gas features and was partitioned into training (70%), validation (15%), and testing (15%) subsets. The classification results show that the baseline classifiers achieved accuracies of 78.4% for SVM, 80.4% for RF, and 83.3% for DNN. Following ABC-based hyperparameter optimization, the optimized Random Forest classifier achieved a significantly improved accuracy of 91.2%. The superior classification performance and robustness of the proposed ABC-optimized Random Forest demonstrate its potential for practical application in reliable and accurate real-world power transformer fault diagnosis.

Keywords Random Forest Artificial Bee Colony Optimization Power Transformer Fault Prediction

Small-Signal Stability Assessment of DFIG-Based Wind Energy Integration in STATCOM-Compensated Nigerian Transmission Network: A Modal Analysis Approach

Dahiru Musbahu — Federal University Of Technology, Minna

G.a. Olarinoye — Ahmadu Bello University, Zaria

Adamu Saidu Abubakar — Ahmadu Bello University, Zaria

Z. Haruna — Ahmadu Bello University, Zaria

A.s Musa — Ahmadu Bello University, Zaria

B.r Tanko — Ahmadu Bello University, Zaria

The increasing integration of Renewable Energy Resources (RESs) into moder power systems presents both operational benefits and stability challenges, particularly in weak transmission networks. This study investigates the impact of Doubly-Fed Induction Generator (DFIG)-based wind energy integration on the small-signal stability of a STATCOM-compensated Nigerian 330 kV transmission network. A modal analysis approach was employed to evaluate system performance under six operating scenarios comprising the base network, STATCOM compensation, and DFIG penetration levels of 5%, 10%, 15%, and 20%. Power flow analysis was conducted to assess network steady state operating conditions, while eigenvalue and damping ratio analyses were used to determine stability characteristics. The results show that moderate wind penetration improves network performance by reducing active power losses and enhancing oscillation damping. The highest damping ratio of 17.81% was recorded at 15% wind penetration, indicating improved stability performance. However, at 20% penetration, a critical low-frequency electromechanical mode associated with generator 12 at Okpai (Bus 38) migrated to the right-half complex, producing a positive eigenvalue and negative damping ratio of -3.64%, thereby indicating small-signal instability. The findings establish 15% wind penetration as the maximum stable operating level for the investigated network configuration. This study provides valuable insights for renewable energy integration planning and highlights the need for supplementary damping control strategies at higher wind penetration levels.

Keywords Keywords: DFIG Wind Energy Integration Small-Signal Stability Modal Analysis STATCOM

A DOMAIN-INVARIANT SPATIO-TEMPORAL GRAPH ATTENTION NETWORK FOR CROSS-DOMAIN ANOMALY DETECTION IN INDUSTRIAL CONTROL SYSTEMS

Emejuo Nichodemus Chibueze — National Research Institute For Chemical Technology (narict), Zaria

Musa Idris Shehu — Ahmadu Bello University, Zaria

Basira Yahaya — Ahmadu Bello University, Zaria

Sani Saleh Saminu — Ahmadu Bello University, Zaria

Mohammed Bashir Abdulrazaq — Ahmadu Bello University, Zaria

Industrial Control Systems (ICSs) are cyber-physical systems responsible for monitoring and controlling critical industrial processes. Their increasing integration with Information Technology (IT) networks, the Industrial Internet of Things (IIoT), and cloud-based services has expanded their exposure to cyber threats, creating a need for intelligent anomaly detection models capable of transferring learned knowledge across heterogeneous industrial environments. However, many existing deep learning-based approaches are developed for individual ICS domains and therefore have limited capability to exploit transferable spatio-temporal patterns across systems with different operational characteristics and feature structures. This study proposes a Domain-Invariant Spatio-Temporal Graph Attention Network (DI-STGAT) for cross-domain anomaly detection in ICSs. The proposed model integrates a Spatio-Temporal Graph Attention Network (ST-GAT) with Domain-Adversarial Neural Network (DANN) learning through a Gradient Reversal Layer (GRL). The ST-GAT captures temporal behaviour and spatial dependencies among industrial process variables, while the DANN/GRL mechanism facilitates domain adaptation by reducing domain-specific information in the learned representations. A fixed-dimensional graph-level representation enables the same model architecture to operate across heterogeneous ICS datasets with different numbers of process variables and graph structures. DI-STGAT achieved cross-domain anomaly detection across heterogeneous ICS environments by combining spatio-temporal graph learning with domain-adversarial adaptation to learn transferable representations from labeled source data and unlabeled target data, thereby improving anomaly discrimination across industrial domains without requiring target-domain anomaly labels for training. The framework was evaluated using the BATADAL, SWaT, and WADI benchmark datasets across six source-to-target transfer scenarios. Experimental results show that DI-STGAT improved mean cross-domain balanced accuracy from 50.51% to 51.90% and mean F1-score from 4.13% to 4.37% compared with the ST-GAT baseline at a fixed decision threshold of 0.50. The strongest improvement was achieved for SWaT→WADI, where balanced accuracy increased from 53.04% to 61.37% and F1-score from 7.48% to 8.94%. The proposed framework achieved mean cross-domain ROC-AUC and PR-AUC values of 72.21% and 36.36%, respectively. Domain-representation analysis further demonstrated measurable adversarial alignment between source and target representations, providing evidence of transferable representation learning across heterogeneous industrial domains. Overall, the findings demonstrate that DI-STGAT provides a viable domain-adaptive spatio-temporal learning framework for cross-domain anomaly detection in heterogeneous ICS environments, supporting more adaptable cybersecurity monitoring and improved protection of critical industrial infrastructure.

Keywords Industrial Control Systems (ICS) Cross-Domain Anomaly Detection Domain Adaptation Spatio-Temporal Graph Attention Network (ST-GAT) Domain-Adversarial Neural Network (DANN) Gradient Reversal Layer (GRL)

DEVELOPMENT AND VALIDATION OF A FINITE ELEMENT MODEL FOR REINFORCED CONCRETE BEAMS EXTERNALLY STRENGTHENED IN FLEXURE WITH STEEL PLATES

Ebitei Williams Francis — Federal University Of Technology, Minna

Auta Samuel — Federal University Of Technology, Minna

Aguwa James — Federal University Of Technology, Minna

Abdullahi Aliyu — Federal University Of Technology, Minna

This study presented and validated a finite element (FE) model for estimating the structural performance of externally flexurally reinforced concrete (RC) beams using bonded steel plates. The developed model was validated with the experimental results, and the effect of the thickness of steel plate and the thickness of adhesive on the ultimate load of strengthened beams was studied. The FE predictions were in good agreement with the experimental results with differences in the ultimate loads being rather minor and the predictions being consistently higher. The developed model was accurate and reliable as indicated by a strong positive correlation (Pearson correlation coefficient, r = 0.961, p < 0.001). The ultimate load was used as a response variable and a two-factor analysis of variance (ANOVA) was conducted. The results showed that the thickness of the adhesive had a statistically significant effect on ultimate load (F = 5.12, p = 0.043) while steel plate thickness did not (F = 2.12, p = 0.201). The load–deflection responses also showed that the RC beams were strengthened considerably when compared to the control RC beam as a result of the application of external steel plate strengthening, in terms of stiffness, energy absorption capacity and ductility. The overall behaviour of the beams with an adhesive thickness ranging from 4 to 6 mm was optimal, showing high stiffness, energy absorption capacity, and high ductility due to the efficient dissemination of the stress on the steel–concrete interface. However, an increased thickness of the adhesive layer (8 mm) in comparison led to a decrease in structural efficiency due to a decrease in the interface stiffness and stress transfer. The study finally shows that the proposed external steel plated RC beam finite element model could be used as a valid tool to predict the behaviour of steel-plated RC beams and that the effect of optimizing the thickness of the adhesive was more significant than the increasing thickness of the steel plates on the RC beam to attain better structural performance.

Keywords Strengthening Load Numerical Beam Stiffness Ductility Energy absorption

From NESI 1.0 to NESI-X: A Hybrid Leapfrogging Architecture for Adaptive Transformation of Nigeria's Electricity Supply Industry

Waliu Musa — Federal University Of Agriculture, Abeokuta

Taiwo Emmanuel Okharedia — Department Of Electrical And Electronic Engineering, Atlantic International University, Hawaii, Usa

Muhammed Ibrahim — Department Of Electrical/electronic Engineering, Federal University Of Petroleum Resources, Effurun, Delta State, Nigeria

Aneke Nnamere Ezekiel — State University Of Medical And Applied Sciences, Igbo-eno Orba, Enugu State, Nigeria

Isaac Adekanye — Operations Manager, Detrio Consult Limited, Lagos, Nigeria

Oluwaseun Adebisi — Department Of Electrical/electronic Engineering, Federal University Of Agriculture, Abeokuta, Ogun State, Nigeria

Umar Abubakar Saleh — Department Of Electrical And Electronic Engineering, Federal University Lokoja, Kogi State, Nigeria

Abstract
More than a decade after the 2013 restructuring and privatization of Nigeria's electricity sector, the Nigerian Electricity Supply Industry (NESI) continues to face interacting technical, commercial, financial, and institutional constraints. Rather than treating recurrent failures as isolated generation, transmission, distribution, metering, or regulatory problems, this paper develops NESI-X as a systemic hybrid-leapfrogging architecture for coordinated transformation. It distinguishes what can be leapfrogged from what cannot: distributed generation, mini-grids, storage, advanced metering, and data-driven operations can bypass selected technological pathways in generation, distribution, metering, monitoring, and maintenance, whereas transmission infrastructure and the institutions that sustain it must be progressively reinforced. Hybrid electricity-sector leapfrogging (HESL) is formally defined as this selective-bypass-plus-reinforcement logic, and the functions it treats as indispensable are named non-bypassable system dependencies (NSDs). NESI-X organizes this distinction into two tiers, transformation capabilities and enabling conditions, coupled through a qualitative causal-loop model and a directed conceptual dependency matrix expressed as expert-informed propositions rather than statistically estimated dependencies. The architecture draws on Nigerian primary regulatory and institutional sources, including the Electricity Act 2023, the National Integrated Electricity Policy, the 2026 Mini-Grid Regulations, FoNER, NISO, and NEMSA's statutory technical-assurance mandate, alongside recent literature on smart metering, mini-grids, digital twins, and cyber-physical security. A gated roadmap and layer-level KPIs are proposed alongside financing, institutional capacity, skills, interoperability, cybersecurity, and political-economy risks as adoption conditions. The contribution is a testable architecture, not a claim of validation.

Keywords Nigeria Electricity Supply Industry hybrid leapfrogging non-bypassable system dependencies distributed energy resources regulatory governance

Integrated HEC-HMS and Improved Soil Moisture Balance Modelling for Groundwater Recharge Assessment in the Semi-Arid Sokoto Basin, Nigeria

Usman Muhammed Kudu — Fut Minna

Richard Adeolu Adesiji — Fut Minna

Groundwater is the primary source of freshwater for domestic, agricultural and livestock activities in the semi-arid Sokoto Basin of northwestern Nigeria, yet increasing water demand, climate variability and limited knowledge of aquifer replenishment have heightened concerns regarding its long-term sustainability. Although several groundwater recharge estimation techniques have been developed, many are either empirical, data intensive or unable to adequately represent the spatial and temporal variability of recharge in data-scarce environments. This study developed an integrated Hydrologic Engineering Center–Hydrologic Modeling System (HEC-HMS) and Improved Soil Moisture Balance (SMB) framework to estimate groundwater recharge within the Sokoto Basin using long-term hydro-meteorological records (1990–2025), observed runoff data, soil hydraulic properties and topographic information. The calibrated HEC-HMS model achieved satisfactory performance with a Nash–Sutcliffe Efficiency (NSE) of 0.516, coefficient of determination (R²) of 0.739 and Root Mean Square Error (RMSE) of 1.433 m³ s⁻¹, indicating reliable runoff simulation. The integrated framework revealed that groundwater recharge is highly seasonal and episodic, occurring predominantly during peak rainfall periods after soil moisture deficits have been satisfied. Spatial analysis further identified distinct high-, moderate- and low-recharge zones controlled by rainfall distribution, soil hydraulic characteristics and land surface conditions. The proposed modelling framework reduces uncertainty in recharge estimation and provides a practical decision-support tool for groundwater resource planning, managed aquifer recharge, watershed conservation and climate-resilient water management in semi-arid regions.

Keywords groundwater recharge hec-hms hydrological modelling semi-arid hydrology soil moisture balance.

Prediction Model for Soil water retention behaviour of unsaturated soils with different Volumetric water content

Abdullahi Karaye — Bayero University Kano

Dr Gambo Haruna Yunusa — Bayero University Kano

Abubakar Jibrin Shuaib — Bayero University Kano

Dr Hafiz Ibrahim — Ahmadu Bello University Kano.

Dr Ibrahim Khalil Umar — Federal University Of Technology, Babura, Nigeria

ABSTRACT
Most of the soils around us exist in an unsaturated state, with various particle composition of
gravel, sand, silt or clay. Clay soils are expansive and are often been subjected to complex hydro-
mechanical circles as they retained lot of moisture. These characteristics exhibited by these types
of soil, lead to structural instability of structures built or constructed on or within them. The aim
of this study is to develop a model for the prediction of the hydro-mechanical behaviour in the
form of matric suction of unsaturated soils with different volumetric water content using some soil
parameters such as; Saturated volumetric water content (Ꝋ), air entry value, Bulk density (Pb),
porosity (n), natural moisture content (w), Plasticity index (P.I), Dry density (ᵨd) and D60 particle
size parameter, and coefficient of permeability(k). A total of 2,550 soils data were used for the
prediction using 6 different models in python environment. Out of the 6 models used, extreme
gradient boost (XGBoost) model shows the best performance. Some of the models used were; Ridge Regression with Train R2
0.6643, Test RMSE 237.8778, cross-validation (CV)
mean R2 of 0.6592, Random Forest with Training R2
of 0.9829, cross-validation,
Test RMSE of 142.8048, (CV) mean R2 of 0.8611, Support vector Regression (SVR) with Training
R2 of 0.1763, Test RMSE of 347.4466, cross-validation (CV) mean R2 of 0.1366,
XGB possess the lowest Test RMSE of 144.3092 with the best training R2, and the best CV performance. These characteristics possessed by the XGBOOST model are
acceptable requirements of a Strong model. The original class values and predicted class values show an
excellent match.

Keywords Unsaturated soils Prediction model Predictors hydro-mechanical behaviour

Systemic Failures and Inefficiencies in Large-Scale Infrastructure Execution: A Critical Appraisal of the Kano–Katsina Road Dualization Project

Aminu Darda'u Rafindadi — Bayero University, Kano

Abubakar Sunusi — Bayero University Kano

Aminu Darda'u Rafindadi — Bayero University Kano

Abdullahi Balarabe Bello

Time overrun remains a severe and chronic problem in the construction sector of developing nations, turning infrastructure investments into financial black holes. This paper critically examines the execution of the 74km Kano–Katsina Road Dualization Project handled by CCECC, leveraging project documents, progress reports, and interim payment certificates. The analysis exposes gross inadequacies in project initiation, financial management, and institutional coordination. Shockingly, by April 2025, the project had consumed 163.33% of its planned time allocation yet achieved only a 90.13% completion rate. This paper delivers a harsh but necessary critique of operational and administrative blunders that drove the project's contract sum from ₦14 billion to an astronomical ₦68 billion and offers constructive, non-negotiable recommendations for future infrastructure management.

Keywords Systemic failure Infrastructure inefficiency Large-scale projects Road dualization Project execution Kano–Katsina Road Construction management Cost overrun Time overrun Quality assurance Contractor performance Procurement process Project deliv

A Security-Constrained Peer-to-Peer Market Framework for Resilient Distribution Networks

Olatunji Obalowu Mohammed — University Of Ilorin

Shereefdeen O. Sanni — Federal University Oye Ekiti, Nigeria

Nabila Ahmed Rufa'í — University Of Birmingham, Uk

Olayinka Sikiru Zakariyya — University Of Ilorin

In the quest to decarbonise, decentralise, and digitalise the global energy systems, the conventional electricity consumers are becoming prosumers. This transition has challenged the traditional centralised utility model and demanded a direct, local energy exchange mechanism. Existing literature has neglected the influence of network security constraints on Peer-to-Peer (P2P) energy transactions. This paper therefore introduces a decentralised market framework designed to facilitate localised energy trading within physical grid constraints. An interior-point optimisation algorithm balances economic welfare and network stability in the proposed framework. P2P outperforms a holistic benchmark against traditional centralised economic dispatch (CED) based on the IEEE 14-bus test system. The results show a net welfare gain of 375.54 m.u./h under the P2P framework; local generation of 57.83 MW compared to 57.97 MW under CED, achieves a lower operational cost (1125.10 m.u./h) and higher total consumer utility (2783.44 m.u./h ) under the proposed P2P market, while nodal voltage profiles remained within the secure operating limit of 1.0206 p.u. Further rigorous testing across different Distributed Energy Resources penetration scenarios shows that the model is stress-resistant for grids. This will provide a scalable and robust solution for modern distribution network operators, where decentralised market clearing discovers previously unavailable network capacity without compromising the network's physical operating limits.

Keywords peer-to-peer energy trading distributed energy resources centralized economic dispatch decentraliuzed market clearing interior point optimization voltage profile distribution network operator

Advancing Sustainable Urban Mobility: A Traffic-Related Air Quality Assessment at Major Road Intersections in Kano Metropolis, Nigeria

Nasiru Danlami — Civil Engineering Department, Bayero University, Kano, Nigeria

Ibrahim Umar Salihi — Civil Engineering Department, Bayero University, Kano, Nigeria

Muttaka Na'iya Ibrahim — Civil Engineering Department, Bayero University, Kano, Nigeria

Urban air quality deterioration driven by vehicular traffic is a critical public health challenge in rapidly growing Nigerian cities. Road intersections represent pollution hotspots where idling, acceleration, and deceleration generate elevated concentrations of harmful pollutants. This study assesses air quality at four major intersections Kano metropolis by evaluating spatial-temporal pollutant variations and compliance with World Health Organization (WHO) and Nigerian Ambient Air Quality Standards (NAQS). Field measurements were conducted for eight weeks at the intersections; NNPC Mega (P1), Kwanar Sabo (P2), Aliko by Maiduguri Road (P3), and Gadar Lado (P4) intersections, with Hotoro GRA serving as a control site (P5). Concentrations of PM₁.₀, PM₂.₅, PM₁₀, CO, NO₂, SO₂, and total volatile organic compounds (TVOCs) were measured twice weekly on Sundays and Mondays during morning, afternoon, and evening periods using a multi-gas detector and air quality monitor. All the 4 sites recorded pollutant concentrations significantly higher than the control site (intersection-to-control ratios: 3.5 – 8.6×). PM₂.₅ was the dominant pollutant, exceeding WHO guidelines (15 µg/m³) by up to 13.9-fold on weekdays. At all the intersections, SO₂ exceeded NAQS limits on both measurement days, and NO₂ at three out of the four intersections exceeded NAQS on Mondays. Weekday concentrations were 49 – 95% higher than weekend values across all parameters. Evening periods consistently produced the highest pollution levels. The signalized 4-way intersection (P2) recorded the highest overall pollution, while the T-junction (P3) recorded the lowest values, suggesting intersection geometry significantly influences pollutant dispersion. Air quality at major intersections in Kano metropolis frequently falls within moderate to severe pollution categories, posing substantial health risks to commuters, pedestrians, and roadside workers. Urgent implementation of intelligent traffic management, vehicle emission controls, and continuous monitoring systems is recommended.

Keywords Air quality assessment traffic-related air pollution road intersections particulate matter Kano metropolis WHO NAQS

Assessment of Groundwater Quality and Irrigation Suitability in Jere LGA, Borno State: Engineering Solutions for Sustainable Agricultural Development in Nigeria

Aliyu Salisu Ibrahim — Ahmadu Bello University, Zaria-nigeria

Muhammad Muhammad Abdulsalam — Agricultural Graduate Association Of Nigeria (agan), Suit B3 Shamras Plaza Opp. Murtala Park Bosso Road, Minna, Niger State-nigeria

Usman Butu Tukur — Ahmadu Bello University, Zaria-nigeria

Abstract
Groundwater is the principal domestic and irrigation water source in Jere Local Government Area (LGA), Borno State, Nigeria, but population growth, agriculture and inadequate sanitation threaten its quality. This study assessed water from five boreholes (BH1-BH5), five hand-dug wells (HW1-HW5) and one lake source (LW1) using physicochemical and bacteriological analyses, Water Quality Index (WQI), and irrigation indices (SAR, Na%, KR, PI and RSC). pH ranged from 6.7-7.5, EC from 420-1,210 µS/cm and TDS from 280-790 mg/L. Nitrate ranged from 12.5-72.6 mg/L, with HW3-HW5 exceeding 50 mg/L. All hand-dug wells and the lake exceeded 5 NTU turbidity and were positive for E. coli, whereas boreholes had turbidity below 5 NTU and no detected E. coli. WQI values of 42.6-57.8 classified boreholes as good, while HW3-HW5 were unsuitable for drinking. All sources were generally suitable for irrigation, but HW3-HW5 were classified as permissible and require active sodium-management measures. Engineering responses include priority boreholes (80-120 m depth; 150 mm PVC casing; gravel pack and sanitary seal), multi-barrier treatment for hand-dug wells, wellhead protection, differentiated irrigation management, and tiered monitoring. These interventions translate the empirical findings into practical measures supporting SDGs 2, 3 and 6.

Keywords groundwater quality engineering solutions water treatment irrigation management borehole design sustainable development

Awareness, Barriers, and Enablers of Circular Economy Adoption in Abuja's Construction Sector: A Survey-Based Assessment

Muhammad Hadi Kabir — Nile University Of Nigeria

Prof. Abdulhameed Danjuma Mambo — Nile University Of Nigeria

Abstract
Construction & Demolition (C&D) waste has been identified as one of the major problems facing rapidly growing cities in Nigeria and has both environmental and economic consequences. The methods through which waste is managed in this industry continue to be largely linear: dispose by default. Circular economy (CE) principles provide a pathway towards sustainable construction; however, their implementation in Nigeria’s construction sector remains poorly researched. This study examines CE awareness, practices, attitudes, and barriers using a cross-sectional survey of 110 construction professionals. A seven-item CE-attitude scale was tested for internal consistency (Cronbach’s α = 0.803). Professional role, years of experience, and educational attainment were examined in relation to CE attitudes and practices using chi-square tests and Spearman correlation. There were no statistically significant differences between professionals' awareness of CE in terms of their professional roles (p = 0.71) or levels of education (p = 0.81). Yet, professionals' roles turned out to be significantly correlated with the frequency of waste separation (χ² = 10.86, p = 0.028) and readiness to engage in CE practices if incentivised (χ² = 11.19, p = 0.025). While contractors and builders were more behaviourally responsive to CE than engineers, there were no statistically significant differences between their levels of awareness of the concept. The quality of recycled materials was found to be the most influential factor when respondents decided to pay for them (ρ = 0.61). The main barriers included the lack of awareness (59.1%), the lack of proper recycling infrastructure (48.2%), and the lack of regulation enforcement (40.0%). Guaranteed markets (49.1%) and technical training (47.3%) appeared to be the most important enablers of CE.

Keywords Circular Economy Construction and Demolition Waste Barriers Enablers Sustainable Construction.

Design and Indigenous Fabrication of a Fixed Bed Reactor for Kerosene Hydrotreating Unit Using Locally Sourced SS304 Stainless Steel

Maryam Abubakar — Ahmadu Bello University

Ibrahim A Mohammed-dabo — Ahmadu Bello University, Zaria

Hydrotreating is an essential refinery process for removing sulphur, nitrogen and other contaminants from kerosene to improve fuel quality and meet environmental standards.This study presents the design and indigenous fabrication of fixed bed reactor for development of a 5 barrel/day kerosene hydrotreating unit using locally sourced SS304 stainless steel, with the aim of promoting local manufacturing capability and reducing dependence on imported process equipment.
The reactor was designed using Aspen HYSYS simulation and validated through manual engineering calculations. Mechanical design was performed in accordance with the ASME Boiler and Pressure Vessel Code. The resulting reactor has an internal diameter of 0.248m, a total volume of 0.0434m³, and a design pressure of 3510.9 kPa. SS304 stainless steel was selected because of its corrosion resistance, mechanical strength, weldability and availability.
The fabricated reactor was successfully constructed using conventional workshop facilities. Dimensional inspection, weld quality evaluation and non-destructive testing confirmed compliance with design specifications and adequate structural integrity for the intended operating conditions.
The study demonstrates that indigenous fabrication of a fixed bed reactor using locally available stainless steel is technically feasible and provides a reliable, cost-effective alternative to imported equipment. The approach supports local content development and offers a practical framework for the manufacture of pressure vessels and process equipment for small-scale refinery applications.

Keywords Fixed bed reactor kerosene hydrotreating indigenous fabrication stainless steel Aspen HYSYS pressure vessel design local content development

Design and Optimisation of a Shell and Tube Heat Exchanger using Particle Swarm Optimisation

Ernest Ikechukwu Dike — Ahmadu Bello University

Umar Hassan — Ahmadu Bello University

Muhammad Auwal Adamu — Ahmadu Bello University

Heavy-duty haulage vehicles operating in tropical environments experience elevated engine oil temperatures that accelerate lubricant degradation and reduce engine reliability. Although Original Equipment Manufacturer (OEM) stacked-plate oil coolers provide compact thermal management, they are prone to irreversible fouling and limited serviceability under prolonged operation. Conventional shell-and-tube heat exchanger (STHE) retrofits offer improved maintainability but are generally oversized and excessively heavy, resulting in increased parasitic mass and reduced fuel efficiency. This study presents the design and optimization of lightweight STHE oil cooler for a Volvo D13 heavy-duty diesel engine using aluminum Alloy 6061-T6. Particle Swarm Optimization (PSO) was implemented in MATLAB to optimize the exchanger geometry, while the Kern design method was employed to evaluate thermal and hydraulic performance. The optimization objective was to minimize the total core weight subject to a maximum shell-side pressure drop of 50 kPa and an overall exchanger length of 1.5 m. The optimized TEMA E-shell configuration comprised 82 straight tubes (18 BWG), a shell diameter of 0.249m, a tube length of 1.471m, a tube outer diameter of 15.0 mm, and a baffle spacing of 0.064m. The resulting design achieved a total aluminum core weight of 23.80kg while maintaining shell-side and tube-side pressure drops of 49.98 kPa and 3.96 kPa, respectively, both within acceptable hydraulic limits for heavy-duty lubrication systems. The exchanger attained a thermal effectiveness of 83.3% with a Number of Transfer Units (NTU) of 2.37, demonstrating efficient heat transfer with low hydraulic resistance. The results confirm that integrating aluminum Alloy 6061-T6 with PSO-based geometric optimization significantly reduces exchanger weight while maintaining high thermal performance and hydraulic reliability. The proposed design provides a lightweight, maintainable, and locally manufacturable alternative to conventional oil coolers for heavy-duty diesel engines operating under demanding tropical conditions.

Keywords shell-and-tube heat exchanger particle swam optimization Volvo D13 heavy-duty haulage

Design and Thermal Performance of a Hybrid Solar-Biomass Dryer for Drying Fish

Igbinosa Ikpotokin — Federal University Otuoke

Fish dryers are heat-transfer devices designed to remove moisture from fish undergoing drying in order improve the fish’s shelf life. However, a dryer that relies only on thermal energy from solar power often perform poorly at night and on cloudy or raining days. These conditions reduce the solar collector’s effectiveness and limit the drying rates. To address this, a hybrid dryer was developed, which uses solar energy as its main heat source and combusts biomass to make up for the absence of solar radiation. This study aimed to create a hybrid solar-biomass dryer that can sustain stable drying conditions regardless of the solar availability. The dryer, which consists of a flat-plate solar collector, biomass combustion chamber, and heat exchanger, was fabricated with low-cost, locally sourced materials. Performance test was conducted outdoors at the Federal University Otuoke, Bayelsa State, using one kilogram of catfish over seven effective daylight hours. To avoid drying interruption, biomass-fueled heating was used in the evening. The results demonstrated that the hybrid dryer reduced the fish drying time from 48 hours to 10 hours and decreased the moisture content from 75% to 15%. The specific energy consumption was 45%, while the average solar collector efficiency was 40%. This study highlights the potential of the hybrid dryer as an effective, economical, and sustainable approach to enhance fish preservation, food security, small-scale business assistance, and reduce post-harvest losses.

Keywords Thermal performance Hybrid dryer Biomass Solar energy Fish drying

development and characterization of carbon dot (CD)-enhanced shea butter as a phase change material for thermal energy storage.

Yotolmbaye Sylvain — Ahmadu Bello University

T.o. Ahmadu — Department Of Mechanical Engineering, Ahmadu Bello University, Zaria

F.o. Anafi — Department Of Mechanical Engineering, Ahmadu Bello University, Zaria

L.o.yusuf — Department Of Mechanical Engineering, Ahmadu Bello University, Zaria

The rapid evolution of thermal energy storage technologies has positioned phase change materials (PCMs) as a cornerstone for advanced heat management and energy conservation systems. The PCMs are distinguished by their ability to absorb, store and release large quantities of latent heat during phase transitions. Organic phase change materials such as shea butter exhibit low thermal conductivity and latent heat of fusion, hence the need to enhance these properties with suitable additives. In this study, carbon dots (CDs) were synthesized hydrothermally with a yield of 40.3% and particle sizes predominantly below 20 nm, before being integrated into pure shea butter. Pure shea butter exhibited low thermal conductivity (0.222577 W/m·K), heat transfer coefficient (37.09621 W/m²·K), latent heat of fusion of 50.50 kJ/kg and specific heat capacity of 0.0184 J/kgoC. Addition of 3wt% CDs to pure shea butter increased thermal conductivity to 0.341 W/m·K, heat transfer coefficient to 56.9 W/m²·K, latent heat of fusion to 173.437 kJ/kg and specific heat capacity to 0.2638J/kg℃. Overall, the composite PCM indicated potential for enhanced thermal storage capacity and heat transfer efficiency, indicating its suitability as a sustainable and cost-effective material for thermal energy storage applications.

Keywords Phase change materials Carbon dots Shea butter hydrothermal synthesis.

Development and Performance Evaluation of a manually operated single raw multi-purpose weeder

Aminu Saleh — Department Of Agricultural And Bio-resources Engineering, Institute For Agricultural Research, Ahmadu Bello University Zaria

Akande F. B — Ladike Akintola University Of Technology, Ogbomoso

Ishola T. A — University Of Ilorin

Weed control is one of the major problems in agricultural production. Most of the peasant farmers in Nigeria use manual weeders in cultivating, a process that is costly, labour intensive and time consuming. Manual weed control does not also give the farmer adequate returns to enable him breakeven. It is, therefore, necessary to design a weeding mechanism that could minimize the human effort and provide efficient work output for the peasant farmer. This study focus on designing, construction and evaluation of a multi-purpose hand-pushed weeding machine that could eliminate the challenges of manual weeding under different field and soil conditions. Materials are selected to suit the construction of the multi-purpose weeder are durable and locally available, easily replaced if damaged and at affordable cost. They include mild steel plate (3mm, 5mm), 30 mm circular (hollow) pipes, 10 mm diameter steel rod, and 40 cm steel and pneumatic wheels to suit different soil conditions. The developed weeder was evaluated in the experimental farm of IAR with impressive results. It works well in loamy (27.42% moisture content) and sandy soils (25.65% moisture content) and requires less labour force compared to the conventional manual hoes. It has an average weeding efficiency of 84.7%, 0.0129ha/hr effective field capacity, 0.019ha/hr theoretical field capacity and 68% average field efficiency. The average cost of the weeder is N42, 000:00.

Keywords Manual weeding hand-pushed weeder weeding efficiency field efficiency

Development of a fault diagnostic and Classification framework for 132 kV capacitor voltage transformer using machine learning techniques

Moses Uchendu — Ahmadu Bello University Zaria

Capacitor Voltage Transformers (CVTs) play a critical role in high-voltage power systems by providing voltage measurements for protection, metering, and monitoring applications. However, their performance can be adversely affected by faults such as capacitor drift, ferroresonance, overvoltage, undervoltage, and insulation degradation, leading to inaccurate measurements and reduced system reliability. The development of intelligent fault diagnosis systems for CVTs is often constrained by the limited availability of comprehensive fault datasets and the severe class imbalance associated with rare fault events. This study proposes an integrated framework for fault diagnosis framework of a 132 kV CVT using machine learning techniques. A high-fidelity CVT model was developed to simulate both normal and fault operating conditions while incorporating temperature variations, harmonic distortion, and measurement uncertainties. A dataset comprising 20,000 samples was generated, containing electrical and operational features including primary voltage, secondary voltage, ratio error, phase error, temperature, and total harmonic distortion (THD). The extracted dataset was subsequently used to develop and evaluate Decision Tree, Support Vector Machine (SVM), k-Nearest Neighbour (kNN), and Ensemble Machine Learning classifiers for multi-class fault prediction. Comparative results demonstrated that the Ensemble classifier achieved superior performance with an accuracy of 99.98%, macro precision of 1.00, macro recall of 0.999, and macro F1-score of 0.999, significantly outperforming the conventional machine learning models. The proposed framework provides an effective solution for accurate fault prediction, improved fault representation, and enhanced condition-based reliability assessment of CVTs, thereby supporting predictive maintenance and improving the operational efficiency of high-voltage power system assets.

Keywords Capacitor voltage transformer machine learning fault diagnosis Support Vector Machine k- Nearest Neighbor Decision Tree Ensemble Classifier

Effect of Superplasticizer Dosage on the Workability and Compressive Strength of Rice Husk Ash Modified Concrete

Yahaya Muhammad — Ahmadu Bello University

Concrete production contributes approximately 5–8% of global anthropogenic greenhouse gas emissions. Using agricultural waste as supplementary cementitious material offers a sustainable approach to reducing cement consumption. This study investigates the effect of superplasticizer dosage on the workability and compressive strength of concrete containing varying proportions of rice husk ash (RHA). RHA was produced by controlled calcination of rice husk at 650°C for 4 hours and characterized using XRF, XRD, and SEM. Concrete mixes contained 0%, 5%, 10%, 15%, 20%, and 25% RHA replacement by cement weight and 0%, 1%, 2%, 4%, 6%, and 8% Conplast SP430 by binder weight. A total of 432 cube specimens (100 mm × 100 mm × 100 mm) were cast and tested at 7, 14, 28, and 56 days in accordance with BS EN 12390-3, while workability was assessed using the slump test (BS EN 12350-2). XRF results confirmed that RHA meets ASTM C618 requirements for Class N pozzolan, with 77.50% combined SiO₂+Al₂O₃+Fe₂O₃ and 4.02% loss on ignition. RHA significantly reduced workability, with slump decreasing from 45 mm to 5 mm at 25% RHA without superplasticizer. Superplasticizer improved workability by up to 287% at 8% dosage. RHA reduced early-age compressive strength, but pozzolanic activity enhanced long-term strength development. The optimum superplasticizer dosage was 6%, beyond which strength declined. The recommended sustainable mix is 10–15% RHA with 4–6% superplasticizer, achieving 28-day strengths of 28.0–31.2 N/mm², suitable for structural applications. The findings provide practical guidance for sustainable concrete production in Nigeria using locally available agricultural waste.

Keywords Rice Husk Ash (RHA) Superplasticizer Compressive Strength Workability Sustainable Concrete Supplementary Cementitious Materials Pozzolanic Reaction Agricultural Waste Nigeria

Enhancing soybean thresher performance: A Taguchi design of experiments approach to modeling threshing and cleaning efficiencies

Abdullahi Saeed Hassan — Abubakar Tafawa Balewa University

Jamilu. M. Ahmed — Abubakar Tafawa Balewa University, Bauchi

Aminu Mohammed — Abubakar Tafawa Balewa University

Danladi Drambi Usman — Abubakar Tafawa Balewa University

Abdulwahab D. Ismail — Abubakar Tafawa Balewa University

Bala Gambo Jahun — Abubakar Tafawa Balewa University

Lawan Garba Abubakar — Abubakar Tafawa Balewa University

The rising global demand for sustainable plant-based proteins highlights the importance of optimizing agricultural processing techniques. Soybean processing, particularly threshing, often relies on traditional, labor-intensive methods that lead to inefficiencies and crop wastage. This study models and optimizes the threshing efficiency (TE) and cleaning efficiency (CE) of a modified soybean thresher using the Taguchi Design of Experiments (DOE). An L-9 orthogonal array was employed to evaluate three primary operational parameters: cylinder speed (500, 600, and 700 rpm), feed rate (3, 4, and 5 kg/h), and concave clearance (10, 13, and 16 mm). The performance evaluation was conducted using TGX 1448-2E soybeans at 12% moisture content (db). Signal-to-noise (S/N) ratio analysis utilizing the "larger-is-better" algorithm identified concave clearance as the most sensitive parameter, followed by cylinder speed and feed rate. The optimal parameter combination for maximum efficiency was determined to be a concave clearance of 13 mm, a cylinder speed of 600 rpm, and a feed rate of 5 kg/h. Furthermore, model analysis demonstrated a significant linear relationship between the operating factors (specifically cylinder speed and feed rate) and threshing efficiency. However, the linear model was found to be inadequate for predicting cleaning efficiency within the established conditions. These findings confirm that the Taguchi method is a robust and resource-efficient tool for optimizing agricultural machinery, contributing to improved post-harvest processing of vital protein crops.

Keywords Soybean thresher Taguchi method Threshing efficiency Cleaning efficiency Parameter optimization.

Experimental Assessment of Activated Charcoal Granules as Wet Pad for Evaporative Cooling in Postharvest Storage Systems Design

Muhammad Abubakar — Waziri Umaru Federal Polytechnic Birnin Kebbi/federal University Of Technology Minna

Olorunsogo Ts — Federal University Of Technology Minna, Nigeria

Mohammed Ibrahim Shaba — Federal University Of Technology Minna, Nigeria

ABSTRACT
Evaporative cooling serves as an energy-efficient alternative to conventional vapor-compression air conditioning. It is a cooling method that uses water to lower air temperature. The conventional cellulose or plastic pads that are mostly used are costly, non-renewable, and require frequent replacement This experimental study was carried out to assess the suitability of charcoal granules as alternative material for evaporative cooling pad used in postharvest storage systems. A test setup is designed to evaluate the performance of charcoal granules. Water absorption and retention characteristics (retention capacity) are critical parameter in evaporative cooling systems, as it directly inﬂuences evaporation rate, cooling eﬀectiveness, operational stability, and overall water consumption. The water retention capacity of the charcoal (internal micro-porosity) was determined to be 0.62 (g/g), with a porosity (bulk void fraction) of 52% The temperature gradients and relative humidity difference were evaluated. The ambient temperature was lowered from an average of 30 – 42°C to 19 – 30°C (ΔT of 10–12°C). Relative Humidity rises from an average of 32%–60% ambient to 75 – 97% inside the chamber. The chamber demonstrates reliable and statistically significant cooling performance, with an average of 24.8% efficiency (8.8°C reduction) across varying ambient conditions. The system delivers consistent temperature drop with substantial moisture addition, reducing sensible heat while slightly lowering (or maintaining) total enthalpy. Performance is consistent across the three days. It is highly effective in humidification, achieving an average relative humidity of 89.48% with 97% efficiency (nearly doubling ambient RH).

Keywords Evaporative cooling charcoal granules cooling pad cooling Efficiency relative humidity efficiency water retention capacity

Experimental Evaluation of a solar dryer integrated with a carbon dot-enhanced shea butter phase change material (PCM).

Yotolmbaye Sylvain — Ahmadu Bello University

T.o. Ahmadu — Department Of Mechanical Engineering, Ahmadu Bello University, Zaria

F.o. Anafi — Department Of Mechanical Engineering, Ahmadu Bello University, Zaria

L.o.yusuf — Department Of Mechanical Engineering, Ahmadu Bello University, Zaria

The increasing demand for sustainable and renewable energy solutions has stimulated significant research into technologies that enhance agricultural productivity and reduce post-harvest losses. Among these technologies, solar drying has emerged as an environmentally friendly and cost-effective method for preserving agricultural products by reducing their moisture content and extending shelf life. Its relevance is particularly pronounced in developing countries such as Nigeria. Phase change material(PCM) are needed to enhance the performance of solar dryers, especially after shine hours. In this study, two solar dryers, with and without PCM, each with a capacity of 2 kg, were constructed and tested alongside open sun drying under average ambient temperature of 28.6 °C and average solar irradiance of 995.5 W/m². The PCM-integrated dryer achieved a drying heat load of 835.81 MJ and an outlet air temperature of 51.6 °C, removing 0.68 kg of moisture with an average drying rate of 0.20 kg/h. The required PCM mass was 3.924 kg (0.0042 m³), providing a thermal energy storage capacity of 489,853 J and enabling extended drying for up to 5 hours beyond sunshine hours. The PCM integrated solar dryer, achieved drying efficiency of 85%. While the non-PCM dryer and open sun drying achieved drying efficiencies of 77% and 40% respectively. This demonstrates superior drying efficiency of the PCM integrated dryer over the other drying methods.

Keywords Phase change material Drying rate Moisture removal Thermal efficiency.

Field-Validated Failure Analysis of Commercial Tricycles in Nigeria and the Potential of Agricultural Residue-Reinforced Aluminium Matrix Composites for Piston Durability Enhancement

Sikiru Kayode Sanusi — The Federal Polytechnic, Offa

Adebisi Jeleel Adekunle — University Of Ilorin/asso. Prof. Department Of Materials And Metallurgical Engineering, University Of Ilorin, Kwara State.

Commercial tricycles are indispensable to the Nigerian transport network, yet their reliability is compromised by recurring mechanical failures whose material origins remain poorly understood. This study integrates a cross-sectional survey of 333 stakeholders, comprising riders, mechanics, and dealers, across six Nigerian states with materials-science analysis to interpret reported faults and identify sustainable intervention strategies. TVS accounted for 73.0% of the fleet. The most prevalent faults were clutch wear (14.2%), piston damage (13.3%), kick-rod fracture (13.3%), frame corrosion (10.0%), and chassis cracking (7.5%). Three primary degradation mechanisms emerged: fatigue-induced fracture, abrasive wear, and substandard components, with 48.6% of respondents attributing failures to these factors. These constitute a self-perpetuating triad that sustains reactive maintenance practices among 59.5% of operators. Logistic regression identified duration of use (AOR = 1.297 per year; p < 0.001) and fairly-used purchase (AOR = 1.887; p = 0.032) as significant predictors of piston damage. The study aims to map component failures, prioritise targets for materials intervention, and establish a foundation for developing agricultural residue-reinforced aluminium matrix composites. Published studies demonstrate the potential of such composites to enhance wear resistance and mechanical properties, yet no work has validated their application under Nigerian tricycle operating conditions. By linking field-reported faults to a viable materials solution, this study provides the empirical basis for designing and testing locally sourced, reinforced pistons for the Nigerian tricycle sector.

Keywords Agricultural-residue Failure-analysis Mechanical-degradation Nigeria Piston-failure Tricycle.

MASS AND ENERGY ASSESSMENT OF THE PYROLYSIS OF LOW LIPID MICROALGAE (DUNALIELLA SALINA)

Yashim Afuwai — Ahmadu Bello University,zaria

Prof. Auwal Aliyu — Department Of Chemical Engineering, Ahmadu Bello University, Zaria

Abstract
As a sustainable and renewable source of energy, microalgae derived biofuel have a growing potential to solve the problem of global energy crisis as a result of high demand for energy, as well as environmental impact such as global warming associated with fossil fuel. Mass and energy assessment of the pyrolysis of low lipid microalgae Dunaliella salina is carried out to produce1kg of bio-oil. A fixed bed tubular reactor was used to carry out direct pyrolysis on the microalgae biomass at . Mass and energy assessment was done to estimate the products yield, mass ratio, energy ratio, energy efficiency, higher heating value (HHV) and energy consumption ratio (ECR) of the biofuel. The maximum yield of bio-oil, bio-char and biogas at were 64.9%, 28.0% and 3.9% respectively. The maximum mass ratio and energy ratio of the bio-oil were 0.649 and 77.98%. The higher heating value (HHV) and energy efficiency of the bio-oil at were obtained as 25.47MJ/kg and 74.50%. The maximum energy consumption ratio (ECR) of the pyrolysis process at was 0.043. The ECR is less 1, which shows that the pyrolysis process is favourable since it exhibits net energy products with high energy content than that required for the reaction to occur. The results obtained from mass and energy balances shows that pyrolysis temperature has a great influence on the distribution yield and energy efficiency of the products. The production of 1kg of bio-oil from the algae biomass feedstock was obtained via pyrolysis of low lipids microalgae.

Keywords Pyrolysis Biomass Microalgae Mass balance Energy balance

Modelling the Dynamic Evolution of Sustainability Risk in Infrastructure Projects: A Bayesian-Calibrated Markov Chain Approach

Emmanuel Adie — Edo State University Iyamho

John Wasiu — Edo State University Iyamho

Ibrahim Abdulrazaq Olayinka — Edo State University Iyamho

Infrastructure projects in socio-ecologically volatile regions are commonly assessed using static risk registers describing risk at a point in time rather than its evolution across the project life cycle. This study models the temporal evolution of socio-economic and environmental sustainability risk in eight Federal Government infrastructure projects in Nigeria's Niger Delta as a discrete-time, finite-state Markov process. Three mutually exclusive states, Low, Moderate and High, were operationalized using six risk indicators. Transition probabilities were estimated through Bayesian synthesis combining Modified Delphi elicitation from 23 experts with empirical transition frequencies from 780 monthly assessments across 15 completed projects, then applied to eight focal projects to generate multi-step forecasts, stationary distributions and Expected Risk Indices. The portfolio converged to 25.8% Low, 42.3% Moderate and 31.9% High risk, an Expected Risk Index of 2.061. Mean escalation probability exceeded mean recovery probability by 41.6%, a persistent tendency toward risk accumulation. Sensitivity analysis indicated generally stable steady-state estimates, though environmentally exposed projects were more sensitive to perturbation. The model correctly classified 94.2% of 778 observed transitions, while a chi-square goodness-of-fit test indicated residual discrepancies between observed and model-expected frequencies, largest for direct Low-to-High transitions, a distinction this paper addresses directly rather than conflating. These findings indicate sustainability risk is better interpreted as an evolving stochastic condition than a static project attribute, and that the Moderate-risk state constitutes a critical intervention window for anticipatory management. The study contributes a mathematically explicit, transparently limited approach for incorporating temporal risk dynamics into sustainable infrastructure governance in data-constrained environments.

Keywords Markov chain model sustainability risk Bayesian calibration stochastic modelling infrastructure projects

Moisture-dependent engineering properties of beedi bambara groundnut (Vigna subterranea (L.) Verdc.) for post-harvest processing design

Abdullahi Saeed Hassan — Abubakar Tafawa Balewa University

Aminu Mohammed — Abubakar Tafawa Balewa University, Bauchi

Jamilu. M. Ahmed — Abubakar Tafawa Balewa University, Bauchi

Bala Gambo Jahun — Abubakar Tafawa Balewa University, Bauchi

Danladi Drambi Usman — Abubakar Tafawa Balewa University, Bauchi

Abdulwahab D. Ismail — Abubakar Tafawa Balewa University, Bauchi

Lawan Garba Abubakar — Abubakar Tafawa Balewa University, Bauchi

he engineering properties of agricultural produce are fundamental requirements for the design and optimization of post-harvest handling, sorting, processing, and storage machinery. This study investigated the physical and mechanical properties of the Beedi Bambara groundnut (Vigna subterranea (L.) Verdc.), a prominent regional cultivar from Bauchi State, Nigeria, as a function of moisture content ranging from 5.0% to 35.0% (wet basis). Over this moisture range, the average linear dimensions—length, width, and thickness—increased from 10.50 to 14.64 mm, 9.49 to 11.65 mm, and 8.50 to 10.90 mm, respectively. The geometric mean diameter similarly expanded from 9.64 to 12.54 mm. Volumetric characteristics, including surface area (245.8 to 390.2〖" mm" 〗^2), seed volume (358.1 to 703.1〖" mm" 〗^3), and 1,000-grain mass (500.2 to 810.5" g" ) exhibited strong positive correlations with moisture content, with the 1,000-grain mass increasing linearly (R^2=0.9987). Conversely, bulk and true densities decreased non-linearly from 1.30 to 1.08〖" g/cm" 〗^3 and 1.32 to 1.18〖" g/cm" 〗^3, respectively, indicating that the seed kernel's volumetric expansion outpaced its mass accumulation. Porosity and the dynamic angle of repose exhibited non-linear variations, peaking at 45.8% and 24.1°, respectively, near 20% moisture content before tapering at higher moisture levels. The static coefficient of friction increased significantly across all structural contact surfaces tested, showing the highest friction on plywood (0.40 to 0.66), followed by galvanized iron (0.30 to 0.52) and aluminum (0.25 to 0.48). These findings demonstrate that the engineering parameters of the Beedi cultivar are highly sensitive to moisture changes, establishing a foundational database necessary for the development of localized cracking, cleaning, and storage equipment.

Keywords Beedi variety Vigna subterranea physical properties mechanical properties structural surfaces geometric mean diameter.

PERFORMANCE EVALUATION OF A PROTOTYPE THERMO-ELECTRIC GENERATOR (TEG) BASED ENERGY HARVESTER FROM ASPHALT PAVEMENTS

Mubarak Danladi Muhammad — Bayero University, Kano

Abdulazeez Nazif — Bayero University, Kano

Asphalt pavements trap a substantial amount of solar radiation and comprise between 30% and 45% of urban areas, thus contributing to the urban heat island (UHI) effect due to their high thermal storage, which leads to the softening and degradation of the pavement. Energy harvesting techniques are one of the promising ways to mitigate these effects while making sustainable use of the trapped thermal energy. In this study, the performance of a thermoelectric generator (TEG)-based energy harvesting prototype integrated with asphalt pavements was evaluated. A fabricated 30 × 30 cm asphalt slab with a thickness of 5 cm and an embedded copper collector was used. The hot side of the TEG module was attached to the L-shaped copper collector, and the cold side was connected to a water-filled aluminium heat sink. Six TEG modules were mounted for redundancy, of which four were active during data collection. Performance was evaluated under controlled indoor conditions; temperatures were measured using embedded thermocouples and electrical output was measured using a multi-meter. Under controlled indoor conditions, temperature differences (ΔT) of 12–22°C produced 0.295–0.897 V, 3.6–15.73 mA, and a maximum power output of 14.12mW from the four active TEG modules, confirming the feasibility of harvesting thermal energy from asphalt pavements. This corresponds to a potential of approximately 157 mW/m² of asphalt pavement surface. The study demonstrates a practical approach to pavement-based thermoelectric energy harvesting in hot-climate regions and recommends outdoor field testing, seasonal performance monitoring, and optimization for large-scale deployment in Kano, Northern Nigeria.

Keywords Heat Sink Seebeck Effect Thermal Collector Conveyor Asphalt Pavement

PRELIMINARY SCREENING AND CHARACTERIZATION OF α-CELLULOSE EXTRACTED FROM COTTON STALK, SUGARCANE BAGASSE, AND SAWDUST USING ALKALINE PRETREATMENT

Hassana Gwandi Audu — Ahmadu Bello University Zaria

Ajayi Olusegun Ayoola — Ahmadu Bello University Zaria

Prof M.t Isa — Ahmadu Bello University Zaria

ABSTRACT
This study investigated the preliminary extraction and characterization of α-cellulose from three lignocellulosic biomass residues: cotton stalk (CS), sugarcane bagasse (SCB), and sawdust (SD), with the aim of identifying suitable pretreatment conditions for subsequent optimization. Preliminary alkaline pretreatment was conducted using NaOH concentrations ranging from 7.5–27.5 g for cotton stalk at 90°C for 1.5 h, and 10–30 g for sugarcane bagasse and sawdust at 95°C for 1.5 h. Sawdust was additionally subjected to a second treatment route involving 7 mL HNO₃ at 95°C for 1.41 h, followed by NaOH treatment at 10–30 g, 95°C for 1.5 h. The resulting α-cellulose samples were evaluated using yield and purity analysis, Van Soest fiber analysis, Fourier Transform Infrared Spectroscopy (FTIR), X-ray Diffraction (XRD), and Scanning Electron Microscopy–Energy Dispersive X-ray (SEM–EDX) analysis. Based on the combined preliminary characterization results, CS2, SCB2 and SD3 were identified as the preferred samples for subsequent optimization. CS2, obtained using 12.5 g NaOH at 90°C for 1.5 h, produced an α-cellulose yield of 30% and purity of 84.06%, while SCB2, obtained using 15 g NaOH at 95°C for 1.5 h, produced a 20% yield and 83.82% purity. SD3, obtained using 20 g NaOH at 95°C for 1.5 h, produced a 60% yield and 85.71% purity. The acid–alkali route produced SDA3 with a higher purity of 90.14% at 20% yield, although the additional acid treatment made SD3 more suitable as the preliminary basis for subsequent optimization. SEM analysis revealed disruption, separation and exposure of fibrous structures following chemical treatment, while EDX demonstrated substantial changes in surface elemental composition between the raw and treated biomasses. These morphological and elemental changes complemented the FTIR and fiber-fraction results in demonstrating enrichment of the cellulose-rich fraction; however, EDX was interpreted as evidence of surface elemental modification rather than direct proof of cellulose purity. XRD analysis showed crystallinity indices of 61.4% for CS2, 59.6% for SCB2, 66.1% for SD3 and 75.2% for SDA3, compared with 61.5%, 55.7% and 51.3% for CS RAW, SCB RAW and SD RAW, respectively. The XRD profiles indicated structural reorganization and the presence of cellulose polymorphic features following treatment. The selected preliminary optimum conditions provide experimental starting points for the subsequent Response Surface Methodology (RSM)–Design of Experiments (DOE)–Central Composite Design (CCD) multi-pulping study, where process variables will be systematically investigated and optimized for each biomass. Furthermore, an Artificial Neural Network (ANN) employing a Feed-Forward Neural Network (FFNN) will be applied in the subsequent stage to predict process responses and evaluate predictive performance. Thus, the study establishes the preliminary pretreatment conditions, α-cellulose yield and purity, and complementary structural, morphological and elemental characteristics required to guide the subsequent statistical and ANN-based optimization of the three biomass systems.

Keywords α-cellulose cotton stalk sugarcane bagasse sawdust alkaline pretreatment

Process Design, Simulation and Performance Evaluation of a 5 BPD Indigenous Kerosene Hydrotreater for Local Refining Capacity Development

Maryam Abubakar — Ahmadu Bello University

Ibrahim A Mohammed-dabo — Ahmadu Bello University, Zaria

Nigeria's drive toward energy self-sufficiency and sustainable industrialization requires the development of indigenous refining technologies that reduce dependence on imported process systems and strengthen local engineering capacity. This study presents the process design, simulation and performance evaluation of a 5 Barrel Per Day (BPD) kerosene hydrotreater, developed for Ahmadu Bello University (ABU) Mini Refinery using locally adaptable technology. The complete hydrotreater process which comprises feed preheating, furnace, fixed bed reactor, product cooling, high pressure and low pressure separators were designed and simulated Using ASPEN HYSYS 8.0 to determine optimal operating conditions and equipment specifications. To simplify the design and reduce cost, the process exclude hydrogen recycle compressors and amine treatment units relying on externally supplied hydrogen to achieve hydrodesulfurization from approximately 0.3 wt.% to below 0.03 wt.%, thereby meeting clean fuel specifications.
Beyond its technical performance, the study demonstrates the potential of indigenous process engineering to support the implementation of Nigeria’s local content policy. As a key component of ABU Mini Refinery, the hydrotreater provides a hands-on learning and research platform that equips students, researchers and practicing engineers with practical skills in process simulation and performance evaluation thereby strengthening indigenous engineering capacity
The study demonstrates the technical feasibility of locally developed refining technologies and highlights their potential to promote workforce development, technology transfer and the growth of a resilient domestic petroleum refining sector.

Keywords Indigenous refining kerosene hydrotreater ASPEN HYSYS process simulation local content engineering education

Reliability Analysis on Reinforced Concrete Column Containing Sawdust Ash for Structural Applications

Cyprian Chukwudi Ogbobe — Federal University Of Technology, Minna, Niger State

Aguwa James — Federal University Of Technology, Minna, Niger State

Abubakar Mahmud — Federal University Of Technology, Minna, Niger State

Kolo Daniel N. — Federal University Of Technology, Minna, Niger State

Abstract
The construction industry faces increasing pressure to adopt sustainable practices, particularly through the utilization of agricultural waste materials as partial replacements for ordinary Portland cement. This study presents a comprehensive reliability analysis of reinforced concrete columns incorporating sawdust ash as a supplementary cementitious material for structural applications. The research investigates the structural performance and reliability of sawdust ash concrete columns through experimental investigation and probabilistic analysis. Sawdust ash, derived from timber industry waste, exhibits pozzolanic properties that contribute to concrete strength development when used at optimal replacement levels. The experimental program involved casting and testing reinforced concrete column specimens with sawdust ash replacement levels ranging from 0% to 20% by weight of cement. Compressive strength tests, flexural strength evaluations, and durability assessments were conducted at various curing ages up to 180 days. The reliability analysis employed first-order reliability methods to evaluate the probability of failure and reliability indices for sawdust ash concrete columns under various loading conditions. Results indicate that sawdust ash concrete at 10% replacement level achieves comparable strength characteristics to conventional concrete while demonstrating improved durability properties. The reliability analysis reveals that sawdust ash concrete columns maintain acceptable reliability indices within the recommended design limits. This research contributes to the growing body of knowledge on sustainable construction materials and provides valuable insights for the practical implementation of sawdust ash in structural concrete applications. The findings support the use of sawdust ash as a viable alternative cementitious material that promotes environmental sustainability without compromising structural reliability and safety.

Keywords Sawdust Ash Reinforced Concrete Column Reliability Analysis Structural Performance Pozzolanic Material

Screening and identification of significant process parameters for solid state fermentation of Trichoderma Harzianum

Buhari Uwairu — Ahmadu Bello University Zaria

Habib Adebisi Abubakar — Ahmadu Bello University Zaria/chemical Engineering Department

Bilal Sabiu — Ahmadu Bello University Zaria/chemical Engineering Department

Agro-industrial wastes have gained considerable attention as inexpensive and renewable lignocellulosic feedstock for the sustainable production of biproducts including bioherbicides, through solid-state fermentation (SSF), an efficient and environmentally friendly biotechnological process. However, maximizing fungal growth and sporulation requires the identification of the most influential process parameters prior to optimization. This study aimed to screen and identify the significant process parameters affecting the solid-state fermentation of Trichoderma harzianum cultivated on agro-industrial residues. Sugarcane bagasse and corncob were selected as the substrates due to their abundance, low cost, favourable physicochemical properties, and proven suitability for supporting the growth and sporulation of Trichoderma harzianum during solid state fermentation. A One-Factor-at-a-Time (OFAT) approach was employed to investigate the effects of substrate weight (5–25 g), moisture content (50–70%), particle size (75 µm–1.18 mm), initial pH (4–8), and inoculum concentration on conidial production. The fermentation was carried out under controlled incubation conditions, and conidial yield (CFU g⁻¹) was used as the response variable. The screening results demonstrated that all the investigated factors influenced fungal growth; however, moisture content, particle size, and initial pH exerted the greatest effects on conidial production. These three factors were therefore selected as the significant process parameters for solid-state fermentation of Trichoderma harzianum. The range of these parameters resulting in substantially higher conidial yields than the other treatment levels were determined to be approximately 55–60% moisture content, particle size around 150–300 µm, and pH 5.0-6.0. The findings provide a scientific basis for identification of and specification of range of values of parameters for optimization of SSF for large-scale production of Trichoderma harzianum as an environmentally friendly bioherbicide.

Keywords Optimization Solid State Fermentation Agro-Industrial Waste Sustainable Agriculture Trichoderma Harzianum Substrate Sugarcane bagasse Corncob

Solar-Biomass Hybrid Systems for Integrated Livestock-Horticulture Farms in Sub-Saharan Africa: A Review

Kouétcha Esaïe Kombetto — Federal University Of Technology Minna

James Garba Ambafi — Federal University Of Technology Minna/department Of Electrical And Electronics Engineering

Taliha A. Folorunso — Federal University Of Technology Minna/department Of Mechatronics Engineering

Integrated livestock-horticulture farms in sub-Saharan Africa depend on costly diesel power while producing manure and crop residues whose energy value is rarely recovered. This review examines how photovoltaic generation and biomass conversion through anaerobic digestion or gasification can be combined into a single farm microgrid. A literature search conducted in Google Scholar on 1 September 2026, covering 2021-2026, returned 43 studies that met the inclusion criteria, 24 of them reporting sub-Saharan African sites or datasets. Every system-level result reported for a solar-biomass hybrid is a simulation. The pairing suits farm conditions: solar output serves daytime irrigation and processing loads, while biogas from on-farm waste provides dispatchable power for the evening peak and heat for brooding, sanitation and cooling. Reported hybrids deliver USD0.265/kWh against USD0.980/kWh for diesel at one Ghanaian site and cut operational CO₂ sharply: from 400 t/yr under a diesel-dominant configuration to 31.8 t/yr at the selected optimum for a Nigerian poultry facility, and from 636 t/yr under diesel-only supply to below 1 kg/yr at a Tanzanian village, all on a combustion-only boundary. Digestate returns to the cropped area as fertiliser. Three design lessons follow. Biogas delivers more value as heat than as electricity at farm scale, so the digester should be sized against thermal demand, allowing for the heat the fermenter consumes. Storage carries the largest share of lifetime cost, so scheduling shiftable loads into the solar window is the most rewarding control measure. Reported profiles, efficiencies and substrate properties vary with site and method, so local characterisation should precede sizing.

Keywords solar-biomass hybrid systems anaerobic digestion farm microgrid dispatch strategy techno-economic analysis sub-Saharan Africa

Upscaling Sustainable Colouration: Design, Fabrication, and Performance Evaluation of an Industrial-Scale Natural Indigo Extraction Machine for Nigeria’s Textile Sector

Adam Muhammad Tanko — Raw Materials Research And Development Council, Abuja

Upscaling Sustainable Colouration: Design, Fabrication, and Performance Evaluation of an Industrial-Scale Natural Indigo Extraction Machine for Nigeria’s Textile Sector
1*Tanko, A. M., 2Abdullahi, S., 2Yakubu, M. K., and 1Ibrahim, H. D.,
1Rawmaterials Research and Development Council, Abuja
2Department of Polymer and Textile Engineering, Ahmadu Bello University, Zaria
*Teebaba04@gmail.com, +2348036469114

Abstract
The reliance of Nigeria’s textile and cottage dyeing industries on imported synthetic colourants poses severe environmental hazards, while the importation of natural indigo dye from Europe and China continues to drain valuable foreign exchange reserves. To drive sustainable import substitution and foster local industrialization, this study presents the design, fabrication, and physical performance evaluation of an indigenous, large-scale natural indigo extraction machine. Batch extraction experiments were carried out to optimize fermentation time, oxidation pH and oxidation time in order to get maximum crude and pure yield as response variables according to central composite design (CCD) using response surface methodology. Fermentation of the plant biomass for 26 hours and aerating the fermented broth for 105 minutes at pH 12 was predicted to result in 29.51 g of crude dye per kg of fresh biomass with a purity of 69.18%. Building upon the optimized batch extraction kinetics, the equipment was engineered to scale up the traditional fermentation and aeration phases into a controlled, high-efficiency mechanical process. Trial runs were conducted five times on the fabricated machine based on the predicted extraction parameters. The results demonstrate a significant reduction in extraction cycle times where up to 100 kg of plant material can be processed at once to give 3.21±1.3 kg of dry indigo flakes with a purity of 71±2.7%, within 30 hours, suitable for industrial dyeing applications. By replacing hazardous synthetic alternatives and bypassing foreign imports, this fabricated system offers a viable, eco-friendly technological pathway to revitalize Nigeria’s historic dye clusters. This research demonstrates how localized engineering design can directly drive sustainable agricultural value addition, environmental protection and economic self-reliance in alignment with national growth objectives.
Keywords: indigo extraction, machinery fabrication, import substitution, sustainable development, natural dyes, textile engineering

Keywords indigo extraction machinery fabrication import substitution sustainable development natural dyes textile engineering

AN ASSESSMENT OF WASTEPAPER MANAGEMENT IN A.B.U. MAIN CAMPUS, SAMARU

Sabur Alim — Ahmadu Bello University, Zaria

Olowodun, Theophilus Mazor — Ahmadu Bello University, Zaria

Wastepaper is paper discarded after being used. Post-consumer paper, or wastepaper, is a vital renewable raw material source for the paper industry and can contribute substantially to the reduction in the importation of paper. With over 45,000 students, about 20,000 staff (academic and non-academic) and 106 departments, Ahmadu Bello University, Zaria, is the largest university in West Africa. With a population of about 200 million people, on the average, a Nigerian use about 10 kg of paper per year. The result showed that for student respondents, 68% between 21-30, 59% are Postgraduate Diploma (PGD) students and 55% have been in ABU for 2-4 years. The demographic results for academic and non-academic staff respondents shows that the 72% are males, 50% of the respondents are single, 40% between 41-50 years and 62% have worked in ABU for 0 to 5 years. 19.8% of the staff and 8% of the students mentioned that reuse of wastepaper is what they do to curb wastepaper generation. The practice among the staff with the highest rank is the burning of wastepaper, while the activity with the least rank is sorting of waste before dumping them into the dustbins. The members of the university community should be encouraged to practice the 3Rs of waste management on waste more than is currently being practiced in the order of reduce, reuse and recycle. The book buyback program should be instituted as one of the methods of mitigating wastepaper generation on campus.

Keywords A.B.U. wastepaper book buyback reduce reuse recycle

AN EVALUATION OF THE MECHANICAL PROPERTIES OF SANDCRETE MORTAR CONTAINING POLYSTYRENE WASTE AND FLY ASH

Salihu Yazeed — Ahmadu Bello University

Sanusi Gambo — Ahmadu Bello University

Abdullahi Getso Ibrahim — Ahmadu Bello University

The increasing accumulation of polystyrene waste and the environmental impact associated with cement production have necessitated the search for sustainable alternatives in the construction industry. The study evaluated the properties of sandcrete mortar containing polystyrene waste and fly ash with a view to developing a lightweight and environmentally friendly material for potential use in non-load-bearing sandcrete blocks. A cement-to-sand mix ratio of 1:6 and a constant water-cement ratio of 0.50 were used to produce the sandcrete mortar cubes of 50x50x50 mm and cylinders of 70mm diameter x100mm height. Fine aggregate was replaced with polystyrene at 0, 5, 10, 15, 20, and 25% by volume, while fly ash was maintained at a replacement level of 10% of cement. In the fresh state, the mixes were tested for consistency using a flow test, while in the hardened state, the sandcrete mortar samples were tested for compressive strength, tensile strength, and density. Furthermore, the morphology of the sandcrete mortar specimens was assessed using Scanning Electron Microscopy (SEM). The results show that the compressive strength of the specimens decreased as the polystyrene content increased from 5 to 25%. However, the mix containing 5% polystyrene and 10% fly ash achieved a compressive strength of 3.125 N/mm² at 90 days, compared with 3.375 N/mm² for the control mix, representing a 7.4% reduction in compressive strength. SEM analysis confirmed a denser cementitious matrix in fly ash-modified mixes due to secondary calcium silicate hydrate (C–S–H) formation, while higher polystyrene contents produced larger interfacial voids that contributed to strength reduction. The 5% polystyrene and 10% fly ash mix was identified as the optimum modified mix, achieving a compressive strength of 3.125 N/mm², exceeding the 2.5 N/mm² minimum requirement reported for non-load-bearing sandcrete blocks under NIS 87:2007, indicating its potential suitability for non-load-bearing applications.

Keywords Fly ash sandcrete blocks polystyrene waste mechanical properties

AN INVESTIGATION INTO THE PHYSICAL PROPERTIES OF METAKAOLIN-BASED GEOPOLYMER MODIFIED ASPHALT BINDER

Kenneth, Ejike Ibedu — Ahmadu Bello University, Zaria

Kenneth, Ejike Ibedu — Department Of Civil Engineering, Baze University, Abuja, Nigeria.

Abdulfatai Adinoyi Murana — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria.

Aliyu Usman — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria.

Abdulmumin Ahmed Shuaibu — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Nigeria.

The development of sustainable, low-carbon construction materials has become a major priority in the construction industry. In response, this study evaluates the effectiveness of metakaolin-based geopolymer (MBG) as a modifier for improving the physical properties of asphalt binder. MBG was incorporated into a 60/70 penetration-grade asphalt binder at dosages ranging from 2% to 10% (by weight of binder, at 2% intervals). The effects on key physical properties including penetration, softening point, ductility, flash point, solubility, and storage stability were systematically investigated. Results showed that MBG addition produced a desirable hardening effect. Penetration decreased by an average of 17.94%, while the softening point increased by 6%, resulting in an improved penetration index. Ductility decreased by 39%, indicating reduced flexibility, whereas the flash point showed a marginal 1% increase. Solubility remained essentially unchanged, and storage stability was satisfactory across the tested range. These enhancements are attributed to strong interfacial interactions between the geopolymer particles and the asphalt matrix, leading to a stiffer and more stable binder structure. Overall, the findings demonstrate the potential of MBG as a sustainable, low-carbon modifier capable of enhancing asphalt binder performance. Based on the results, a 2% MBG dosage is recommended as the optimal level for effectively improving the physical properties without excessive compromise to ductility.

Keywords Asphalt binder Metakaolin Geopolymer Physical properties Sustainability

Development and Characterization of Hydrophobic Silica Aerogel Synthesized from Rice Husk via Ambient Pressure Drying

Isa Zubairu — Department Of Civil Engineering, Abubakar Tafawa Balewa University, Bauchi, Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria Nigeria & Faculty Of Civil Engineering, University Teknologi Malaysia

Badruddeen Saulawa Sani — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria, Nigeria

Salmiati Salmiati — Department Of Environmental Engineering, Faculty Of Civil Engineering, Universiti Teknologi Malaysia, 81310 Utm Skudai, Johor Bahru, Malaysia

Umar Alfa Abubakar — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria, Nigeria

Sunday Bamidele Igboro — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria, Nigeria

Aliyu Ishaq — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University Zaria, Nigeria

Silica aerogels are ultra-lightweight, highly porous nanostructured materials with high specific surface area, properties that make them attractive adsorbents for water and wastewater treatment. However, conventional silica aerogels are commonly produced from costly precursors such as tetraethyl orthosilicate (TEOS), limiting their large-scale application, particularly in resource-constrained settings. This study reports the development of a hydrophobic silica aerogel from rice husk, an abundant and low-cost agricultural by-product, and its comprehensive physicochemical characterization. High-purity amorphous silica was extracted from rice husk via acid leaching and calcination, converted to sodium silicate through alkaline digestion, and processed into a gel via acid-catalyzed sol-gel synthesis. The resulting hydrogel beads were solvent-exchanged into ethanol, surface-modified with trimethylchlorosilane (TMCS) to confer hydrophobicity, and dried at ambient pressure. The synthesized aerogel was characterized using nitrogen adsorption-desorption (BET/BJH/t-plot), Fourier-transform infrared spectroscopy (FTIR), water contact-angle goniometry, bulk density/porosity determination, and scanning electron microscopy (SEM). The aerogel exhibited a BET specific surface area of 303.60 m²/g, a mesoporous structure with pore diameters of 3.37–3.40 nm and pore volume of 0.52 cm³/g, negligible microporosity, a superhydrophobic water contact angle of 155.70° ± 1.34°, a bulk density of 0.18 g/cm³, and porosity of approximately 92%. FTIR confirmed characteristic Si-O-Si and Si-OH functional groups, while SEM revealed a rough, porous, agglomerated morphology consistent with an ambient-pressure-dried aerogel network. These results demonstrate that rice husk is a viable, sustainable precursor for producing hydrophobic, mesoporous silica aerogel with textural and surface properties suitable for adsorption-based water treatment applications.

Keywords silica aerogel rice husk sol-gel synthesis ambient pressure drying hydrophobicity

DYNAMIC MECHANICAL ANALYSIS OF RECYCLED LDPE/HDPE POLYMER BLENDS

Tijani Abdullahi — Ahmadu Bello University Zaria

Tajudeen Bello — Ahmadu Bello University Zaria

Abdulmalik Dahiru Kona — Ahmadu Bello University Zaria

This study investigated the dynamic mechanical behaviour of blended low-density polyethylene (LDPE) and high-density polyethylene (HDPE) waste plastics using Dynamic Mechanical Analysis (DMA). The aim was to evaluate the effect of HDPE loading on the viscoelastic and damping properties of LDPE/HDPE blends. Samples with varying HDPE loadings (0–50 wt.%) were prepared by melt compounding on a two-roll mill machine, followed by compression moulding. DMA was conducted at a frequency of 1 Hz over a temperature range of 30–120 °C at a heating rate of 6 K/min. The results showed that increasing HDPE content significantly improved the mechanical performance of the blends. Relative to pure LDPE, the storage modulus increased by approximately 573%, while the loss modulus increased by approximately 422% at 50 wt.% HDPE loading. The tan δ values ranged from 0.13 to 0.27 across all blends within the investigated temperature range of 30–120 °C, indicating good damping characteristics. The findings demonstrate that HDPE incorporation enhances the stiffness and mechanical strength of LDPE-based blends, indicating the potential of recycled LDPE/HDPE waste plastics for engineering and structural material applications.

Keywords High-density polyethylene (HDPE) low-density polyethylene (LDPE) plastics polymer blend Dynamic mechanical Analysis (DMA).

Effect of Alkaline Pre-treatment on the Mechanical Strength and Biodegradation Behaviour of Coir Fibre Reinforced Concrete

Oluwatobi Akin — Ahmadu Bello University, Zaria

Ibrahim Aliyu — Ahmadu Bello University, Zaria

Bilkisu Amartey — Ahmadu Bello University, Zaria

Amana Ocholi — Ahmadu Bello University, Zaria

Concrete is widely recognized for its high compressive strength, yet it suffers from low tensile capacity, brittleness and susceptibility to cracking under cyclic loading. Coir fibre offers a renewable and low-cost means of improving toughness; however, its high water absorption and vulnerability to alkaline and microbial attack limit long-term durability. This study examined the influence of NaOH pre-treatment on the workability, mechanical properties and biodegradation resistance of coir fibre reinforced concrete (CFRC). Fibres treated with 0, 5 and 10 % NaOH were incorporated at 0.5, 1.0 and 1.5 % by cement weight. Slump, compressive, flexural and split tensile strengths were determined, while fibre biodegradation was evaluated through soil-burial testing for up to 56 days. Workability decreased with increasing fibre content and alkali concentration. The combination of 1 % fibre and 5 % NaOH produced the highest mechanical strengths (22 N/mm² compressive, 4.25 N/mm² flexural and 2.89 N/mm² splitting tensile) together with the lowest mass loss (2.24 % after 56 days), compared with nearly 29 % for untreated fibre. Moderate alkaline treatment at 5 % NaOH with 1 % fibre therefore offers a practical balance of strength and durability for sustainable coir-fibre concrete.

Keywords Coir fibre Alkaline pre-treatment Concrete Biodegradation

Engineering Sustainable PCL/PLA/HAp-Sr/Keratin Fibre Biopolymer Composites for Bone Tissue Engineering Applications: Mechanical and Chemical Properties

Kazeem Salami — Ahmadu Bello University

Abdulmumin Akoredeley Alabi — Ahmadu Bello University

Ibrahim Iliyasu — Ahmadu Bello University

Muhammad Auwal Adamu — Ahmadu Bello University

Abdulaziz Abdullahi Bada — Ahmadu Bello University

Polycaprolactone (PCL) is widely recognised as a promising biomaterial owing to its ease of processing, biocompatibility, and biodegradability. Despite these advantages, its slow degradation rate and insufficient mechanical strength and stiffness hinder its application where enhanced structural performance is required. This study investigates the influence of PLA, strontium-doped hydroxyapatite (HAp/Sr), and keratin fibre reinforcement on the chemical structure and mechanical performance of polycaprolactone (PCL)-based biocomposites. FTIR spectroscopy was employed to examine molecular interactions between the polymer matrix and reinforcing phases. The tensile strength, Young's modulus, hardness and fracture toughness tests were conducted to evaluate mechanical integrity. The spectra show the presence of PCL through characteristic absorption bands at 2947 and 2865 cm-1, attributed to the C-H asymmetric stretching vibration. A slight shift is observed in some peaks toward either a lower or a higher wavenumber, with no new peaks observed in the reinforced biocomposites. This indicates that the HAp/Sr and keratin fibre functional groups are located within the polymer structures. Pure PCL (BC1) exhibited the lowest mechanical performance, with an ultimate tensile strength of 0.0455, Young’s modulus of 0.02, hardness of 22.3, and fracture toughness of 0.5659. Incorporation of reinforcing agents (i.e., PLA, strontium-doped hydroxyapatite (HAp/Sr), and keratin fibre) resulted in a significant increase in hardness and fracture toughness, demonstrating the reinforcing effect of bioactive fillers. The sample BC4 showed the highest overall mechanical performance, with ultimate tensile strength (0.385), Young’s modulus (0.0405), hardness (56.33), and fracture toughness (1.0534), indicating enhanced stiffness and resistance to crack propagation. These findings suggest that the synergistic combination of PLA, keratin fibre, and bioactive ceramic additives significantly enhances the mechanical behaviour of PCL-based materials, making them more suitable for applications requiring improved strength, stiffness, and durability, such as biomedical scaffolds and load-bearing structures.

Keywords Polycaprolactone Polylactic Acid Keratin Fiber Hydroxyapatite Mechanical properties

Engineering Sustainable Solid Biofuels for Nigeria's Clean Energy Transition: Comparative Performance Evaluation of Individual and Blended Agro-Residue Briquettes

Binta Zakari Bello — Ahmadu Bello University Zaria

Rabiu Kamaldeen — Ahmadu Bello University Zaria

Aisha Talatu Ibrahim — Ahmadu Bello University Zaria

Nigeria’s transition toward a sustainable, low-carbon energy system necessitates decentralized engineering solutions capable of converting abundant agricultural residues into clean, high-performance solid biofuels. This study presents a comparative experimental evaluation of solid biofuels engineered from maize straw, rice straw, wheat straw, and selected binary blends, characterized across 18 distinct formulations using cassava starch, Gum Arabic, and coal tar as binders under compaction pressures of 5 and 10 MPa. Characterization included higher heating value (HHV), ash content, moisture content, compressive strength, ignition time, burning rate, and water resistance index (WRI). Two-way Analysis of Variance (ANOVA) and Pearson correlation analyses demonstrated that biomass composition is the primary determinant of thermal behavior and ash characteristics. The 50:50 maize–wheat straw blend bonded with coal tar at 5 MPa (5M5Wc5) recorded the highest HHV (20.5 MJ kg⁻¹), the shortest ignition time (10 s), and a relatively low ash content (7.0%). The highest compressive strength was recorded by the Gum Arabic-bonded wheat straw formulation Wg5 (206.9 kN m⁻²). Across the full dataset, ash content was negatively associated with HHV (r = −0.696), whereas the correlation between compressive strength and WRI is also negative at r = - 0.29. In Phase II, exploratory two-way ANOVA without replication indicated a statistically significant main effect of compaction pressure on moisture content (p = 0.0017), but not on compressive strength (p = 0.6175); interaction effects could not be independently estimated. The results demonstrate application-specific trade-offs among thermal performance, mechanical integrity, moisture resistance, and environmental considerations. By converting agricultural residues into value-added solid fuels, the study supports resource recovery and circular-bioeconomy pathways while providing an engineering basis for decentralized biomass-energy systems in Nigeria.

Keywords Biomass densification Binder characteristics Rice straw Wheat straw Maize straw Waste Valorization Circular Bioeconomy

ENHANCING THE THERMAL PROPERTIES OF ASPHALT PAVEMENT FOR ELECTRICITY GENERATION USING THERMOELECTRIC GENERATORS.

Farouk Shehu Yakasai — Bayero University Kano

Aminu Suleiman — Bayero University Kano

Abstract: Asphalt pavements absorb substantial amounts of solar heat, much of which remains unutilized despite its potential for renewable electricity generation through thermoelectric generators (TEGs), making the enhancement of asphalt thermal properties essential for improving temperature gradients and energy harvesting efficiency. This study evaluates the use of steel slag, an industrial by-product, as a partial replacement for natural coarse aggregates to enhance the thermal performance of asphalt concrete, with mixtures designed using the Marshall Mix method at steel slag replacement levels ranging from 0% to 25%. Laboratory tests measuring thermal conductivity, specific heat capacity, and thermal diffusivity were performed and verified using a three-dimensional transient heat transfer model in Abaqus, and all mixtures satisfied ASTM D6927 requirements with an optimum binder content of 6.0%. The findings indicate that incorporating steel slag significantly improves thermal performance, with 5% replacement yielding the highest thermal conductivity (3.0421 W/mK) and the lowest specific heat capacity (794.5 J/kg•K), demonstrating that limited steel slag inclusion, particularly at 5%, enhances asphalt thermal behavior and supports its suitability for pavement-integrated thermoelectric energy harvesting systems.

Keywords Asphalt Concrete Thermoelectric generators (TEG) Energy harvesting Thermal properties Steel slag 3D Finite element.

Evaluation of the synergistic effect of Corncob Ash (CCA) and Date Palm Seed Ash (DPSA) as partial cement replacement on the mechanical properties of concrete.

Tukur Sani — Ahmadu Bello University, Zaria.

Yusuf Yau — Ahmadu Bello University, Zaria.

Tasiu Ashiru Sulaiman — Ahmadu Bello University, Zaria.

Yusuf Mansur Hashim — Ahmadu Bello University, Zaria.

The production of Ordinary Portland Cement (OPC) is associated with high carbon dioxide emissions and energy consumption, creating the need for sustainable supplementary cementitious materials. This study investigated the synergistic effect of Corncob Ash (CCA) and Date Palm Seed Ash (DPSA) as partial cement replacements on the mechanical properties of concrete. CCA and DPSA were produced through controlled calcination at 650–750°C and incorporated as binary (OPC–CCA and OPC–DPSA) and ternary (OPC–CCA–DPSA) blends at replacement levels of 5, 10, 15, and 20% by weight of cement. 117 cubes of 100x100x100mm and 78 cylinders of 100x200mm Concrete specimens were designed for a target compressive strength of 30 MPa with a water–cement ratio of 0.50, cured for 7, 14, and 28 days and tested for compressive and split tensile strengths in accordance with relevant British Standards. Strength increased with curing age for all mixes, with the binary blends outperforming the ternary blend. At 28 days, OPC–CCA and OPC–DPSA achieved optimum compressive strengths of 32.33 MPa and 32.00 MPa, respectively, at 5% replacement, while the ternary blend attained 28.33 MPa. OPC–DPSA recorded the highest split tensile strength of 3.61 MPa at 10% replacement, whereas the ternary blend reached 3.50 MPa. Higher replacement levels (15–20%) reduced strength due to the cement dilution effect. The study concludes that 5–10% replacement is optimal. Although the expected synergistic enhancement of the ternary blend was not fully realized, longer-term curing may improve its performance. Overall, CCA and DPSA show strong potential as sustainable supplementary cementitious materials that reduce cement consumption while maintaining satisfactory mechanical properties.

Keywords Corncob ash Date palm seed ash Supplementary cementitious materials Compressive strength Split tensile strength Sustainable concrete.

EXPERIMENTAL VALIDATION OF EUROCODE 2 PREDICTIONS FOR THE FLEXURAL AND SHEAR CAPACITIES OF REINFORCED METAKAOLIN-BASED GEOPOLYMER CONCRETE BEAMS

Ibrahim Aliyu — Ahmadu Bello University, Zaria

Idayat Oluwakemi Sholadoye — Department Of Civil Engineering, Ahmadu Bello University, Zaria

Idris Abubakar — Department Of Building. A.t.b.u. Bauchi

Jamilu Yau — Department Of Civil Engineering, Ahmadu Bello University, Zaria

Abubakar Abbas Aliyu — Bankanu And Partners Limited, Suite 001, Basement Level, Mortgage House, C.b.d Abuja

Sustainable construction materials research, including geopolymer concrete, has been ongoing for quite some time. This is because they are environmentally friendly and can be employed as alternatives to ordinary Portland cement (OPC) concrete. The researchers have been pushing for the adoption of geopolymer concrete as an alternative to OPC concrete in structural members’ production. However, the applicability of existing reinforced concrete design provisions to reinforced metakaolin-based geopolymer concrete (MBGC) beams was not adequately validated. This study experimentally investigated the flexural and shear capacities of singly reinforced MBGC beams and compared the results with values predicted using Eurocode 2 (EC2). Three beams were produced, each with two 8, 10, and 12 mm tensile reinforcements (RGCB08, RGCB10, and RGCB12 respectively), and were tested to failure under static loading; the experimental ultimate moment and shear capacities were compared with EC2 theoretical values. The results showed that increasing the reinforcement ratio enhanced both flexural and shear performance. Compared with RGCB08, the experimental ultimate moment increased by 10% and 26% for RGCB10 and RGCB12, while the corresponding EC2-predicted moment increased by 28.7% and 41.7%. The EC2 moment capacity predictions were in close agreement with the experimental capacities, with experimental-to-theoretical moment ratios of 1.11, 0.95, and 0.99 (≅1.0), respectively, for the three reinforcement ratios. In contrast, the experimental-to-theoretical shear ratios were 2.9, 2.9, and 3.4 for RGCB08, RGCB10, and RGCB12, respectively, indicating that the experimental shear capacities exceeded the EC2 predictions. The conservative shear predictions were attributed to EC2 limitations on the longitudinal reinforcement ratio and effective depth factors for beams without shear reinforcement. The study concludes that despite EC2 underestimating the measured shear capacity, its predictions remain conservative and provide a safe design. EC2 is therefore recommended for the flexural and shear design of reinforced metakaolin-based geopolymer concrete.

Keywords MBGC Reinforced concrete beams Eurocode 2 (EC2) Flexural capacity Shear capacity Reinforcement ratio.

Influence of Plastic Waste Morphology on the Compaction Properties of Marginal Lateritic Soil

Ahmad Idris — Bayero University

Aminu Suleiman — Bayero University

Gambo Haruna Yunusa — Bayero University

The incorporation of plastic waste, encompassing various types of plastic materials, into lateritic materials presents a significant opportunity to address plastic pollution while simultaneously improving the engineering characteristics of the fill material. This study investigated the change in compaction properties of a marginal lateritic soil mixed with varying contents of two different forms of Plastic Waste. Samples of used water bags popularly known as sachet water bags for this study were collected from Kano State, Nigeria and prepared as fi-bers (i.e cut in to pieces of not more than 5mm width and 25mm length) and powder (grinded to a powdered form). Lateritic soils used as fill material in ru-ral roads construction were mixed with 0-15% of each of the prepared plastic waste and tested in the laboratory to determine the Maximum dry Density MDD and Optimum Moisture Content (OMC). The results obtained from the tests show that the powdered form reduced maximum dry density of the soil from 1.94 g/cm3 at 0% to 1.33 g/cm3 at 15% plastic, while the fiber form caused less-er density reductions. Optimum moisture content increased more prominently for both forms up to 18.41% with the fiber and 17.51% for powdered. Plastic waste usage shows potential; however, it is essential to investigate optimal types and content ratios. The powdered form decreases strength at elevated dos-ages, whereas the fiber form improves strength at dosages up to 5%. This study demonstrates that the incorporation of Sachet Water Plastic Waste (SWPW) in altering the characteristics of lateritic fill material can effectively tackle Nigeria's plastic waste challenges while highlighting sustainable construction methodologies.

Keywords Plastic Waste Fiber Content Soil Stabilization Geotechnical Properties

Influence of T6-Aging Treatment on Selected Mechanical Properties of Aluminium Alloy A356/Melon Husk Ash Nanocomposite.

Ibrahim Usman — Ahmadu Bello University, Zaria

Kamilu Adeyemi Bello — Ahmadu Bello University, Zaria

Malik Abdulwahab — Ahmadu Bello University, Zaria

Terver Ause — Ahmadu Bello University, Zaria

Aluminum matrix nanocomposites are gaining prominence in automobile manufacturing due to their competitive properties, which can be further improved through heat treatment of the composites. The present study explores the effect of T6-aging treatment on the mechanical properties of a novel aluminium-based nanocomposite, namely A356 reinforced with melon husk ash nanoparticles (A356/MHAnp). Melon husk ash (MHA) nanoparticles, produced from an abundant Nigerian agro-waste—Egusi melon (Citrullus colocynthis L.) husks—were used to reinforce A356 aluminium alloy through a low-frequency vibration-assisted stir casting technique. Samples of the cast nanocomposite and the unreinforced alloy were subjected to T6-aging heat treatment, after which hardness and tensile properties were determined using standard test procedures. X-ray diffraction (XRD) and optical microscopy (OPM) were used to study the microstructure of the samples. XRD patterns of the nanocomposite samples revealed the presence of α-Al, Si, β-Al5FeSi, Mg2Si, and SiO2, while optical micrographs revealed a refined microstructure comprising primary α-Al dendrites, acicular Si, and a relatively even distribution of nanoparticles within the matrix of the heat-treated nanocomposite samples. Results of the mechanical tests showed that the T6-heat-treated nanocomposite exhibited improved properties over both the as-cast nanocomposite and the unreinforced samples. The tensile strength of the sheat-treated nanocomposite (180.79 MPa) represented an improvement of 24.87% over the as-cast nanocomposite and 53.42% over the as-cast unreinforced sample. The ductility of the heat-treated nanocomposite (6.63%) represented a 22% improvement over the as-cast nanocomposite and a 32% improvement over the as-cast alloy. Meanwhile, the hardness value of the heat-treated nanocomposite (127.14 HV) represented an improvement of 0.9% over the as-cast nanocomposite and 55% over the as-cast alloy. In summary, the study demonstrates that MHA nanoparticles are a viable and effective reinforcement for aluminium matrix composites, and that T6-aging heat treatment offers a sustainable pathway for enhancing their mechanical properties.

Keywords T6 heat treatment melon husk ash aluminium matrix nanocomposite agro-waste mechanical properties

MARSHALL PROPERTIES OF HIGH-RAP HOT MIX ASPHALT INCORPORATING LDPE-MODIFIED BITUMEN AND WASTE ENGINE OIL REJUVENATOR

Abdulmumin Ahmed Shuaibu — Department Of Civil Engineering, Ahmadu Bello University, Zaria

Mudassir Rabiu Adam — Department Of Highway Engineering, Federal University Of Transportation, Daura

Ahmad Abdulsalam Amin — Department Of Civil Engineering, Ahmadu Bello University, Zaria

Esther Amanosi Nyebe — Department Of Civil Engineering, Ahmadu Bello University, Zaria And School Of Civil Engineering, University Of Manchester, Oxford Road, Manchester, Uk

Asmau Hamdana Kankia — Office Of The Secretary Of Kaduna State Government, Kaduna State.

Abdulmumin Nda Mohammed — Department Of Civil Engineering, Ahmadu Bello University, Zaria, Department Of Civil Engineering Faculty Of Engineering, Baze University, Abuja.

Ismaila Mohammed Amodu — Department Of Civil Engineering, Ahmadu Bello University, Zaria And Julius Berger Nigeria, Ltd, Abuja, Nigeria

The use of Reclaimed Asphalt Pavement (RAP) in Hot Mix Asphalt (HMA) is a result of the growing need for economical and environmentally friendly road construction solutions. When old asphalt is removed for resurfacing and reconstruction, RAP is created. Furthermore, the rise in plastic garbage in recent years has become a major ecological problem on a global scale. Therefore, this study explores the use of High RAP content, Waste Engine Oil (WEO) as a rejuvenator and Low-Density Polyethylene (LDPE) as a bitumen modifier in hot mix asphalt. Preliminary physical property testing was conducted on the hot mix asphalt constituent materials (bitumen and mineral aggregates) in accordance with relevant standards. The Marshal mix design was employed to determine the optimum binder content using virgin materials (at no RAP and EPS contents), with bitumen content between 5% and 7% at 0.5% intervals, as outlined in the Nigerian General Specification for Roads and Bridges. Furthermore, RAP was utilized to replace the virgin coarse aggregates by weight (25%, 50%, 75%, and 100%) at the optimal binder content modified with LDPE at varying replacement of 4%, 8%, and 12%. A 15% of waste engine oil by weight of the optimum binder content was added to the mix as rejuvenator. The physical properties of these materials aligned with the relevant code specifications, and the optimal binder content was established at 6.5% while the most effective modified asphalt mix was determined at 4% LDPE modified bitumen and 75% RAP incorporation.

Keywords Marshall Properties Reclaimed asphalt Low-Density Polyethylene hot mix asphalt waste engine oil

Mechanical and Durability Performance of Sustainable Concrete Incorporating Rice Husk Ash and 100% Recycled Concrete Aggregate

Raphael Ejembi — Ahmadu Bello University, Zaria

Amana Ocholi — Ahmadu Bello University, Zaria

Bilkisu Amartey — Ahmadu Bello University, Zaria

Williams Ejembi — Ahmadu Bello University, Zaria

Samuel Ebiojo Ocheja — Ahmadu Bello University, Zaria

Samuel Godwin Obademi — Ahmadu Bello University, Zaria

Sumaila Muhammed Shaibu — Department Of Water Resources And Environmental Engineering, Ahmadu Bello University, Zaria

This study evaluated the Mechanical and Durability Performance of Sustainable Concrete Incorporating Rice Husk Ash and 100% Recycled Concrete Aggregate. The materials used in the course of this research include; Portland Limestone Cement, Rice Husk Ash, Fine Aggregate (River sharp sand), Recycled Concrete Aggregate and clean water. From X-ray Fluorescence test, the Rice Husk Ash contained 89.47% of [(SiO₂) + (Al₂O₃) + (Fe₂O₃)] making it a good pozzolan. Normal vibrated concrete was produced as control from earlier designed grade 25 (G25) concrete. Cement was replaced with Rice Husk Ash (RHA) at 10%, 15%, and 20% and coarse aggregate was completely replaced with Recycled Concrete Aggregate. Unlike many previous research that studied these materials independently or limited recycled concrete aggregates (RCA) to small amounts, this research evaluates feasibility of producing structural concrete using 100% RCA in combination with varying amounts of RHA in partial replacements for cement. The 28 days compressive strength for 10%, 15%, and 20% of RHA are 20.1 N/mm², 25.9 N/mm², 19.9 N/mm² respectively. The 15% cement replacement gave the optimum compressive strength with a corresponding tensile strength of 2.5 N/mm². The Water Absorption capacity of the 15% cement replacement concrete was 1.23% which is within the specifications of BS 812: part 2 (1995). It is found that the optimum mechanical properties like compressive strength, water absorption capacity of the concrete were achieved at 15% cement replacement level.

Keywords Rice husk ash (RHA) Recycled concrete aggregate (RCA) Sustainable concrete Supplementary cementitious material Compressive strength Splitting tensile strength Water absorption.

Optimization and Predictive Modelling of Doum Palm Fibre-Reinforced Concrete Incorporating Rice Husk Ash

Musa Abdullahi — Ahmadu Bello University, Zaria

Yusuf Yau — Ahmadu Bello University, Zaria

Isah Garba — Ahmadu Bello University, Zaria

Bashir Usman — Nuhu Bamalli Polytechnics, Zaria

Suleiman Yusuf — Nuhu Bamalli Polytechnics, Zaria

The growing demand for environmentally sustainable construction materials has stimulated interest in incorporating agricultural waste products into concrete production. This study investigates the mechanical performance and optimization of doum palm fibre (DF)-reinforced concrete containing rice husk ash (RHA) as a partial replacement for Portland limestone cement. A multilevel factorial experimental design based on Response Surface Methodology (RSM) was employed to evaluate the combined influence of RHA replacement (0–25%) and DF content (0–2%) on compressive strength, flexural strength, split tensile strength, and punching shear strength. Predictive regression models were developed using Design-Expert software and assessed through analysis of variance (ANOVA), coefficients of determination (R²), and residual diagnostics. Quartic polynomial models adequately represented all responses, with coefficients of determination ranging from 0.9656 to 0.9914. Numerical optimization identified an optimum mixture containing 2.0% DF and 10.45% RHA, producing predicted compressive, flexural, split tensile, and punching shear strengths of 18.01 MPa, 5.37 MPa, 4.42 MPa, and 1.05 MPa, respectively, at 56 days. Experimental validation showed prediction errors below 5%, confirming the reliability of the developed models. The findings demonstrate that response surface methodology provides an effective tool for optimizing sustainable fibre-reinforced concrete mixtures while reducing experimental effort. The combined use of rice husk ash and doum palm fibre offers a viable approach for producing environmentally friendly concrete with satisfactory mechanical performance.

Keywords Response Surface Methodology compressive strength flexural strength split tensile strength punching shear strength rice husk ash doum palm fibre regression models

Optimization of Organosolv Lignin Extraction from Groundnut Shell for Adhesive Precursor Applications

Mustapha Nma Abubakar — Ahmadu Bello University Zaria

Prof M.t Isa — Ahmadu Bello University Zaria

Tajudeen Bello — Ahmadu Bello University Zaria

Adamu Yusuf — Ahmado Bello University Zaria

Bello Abdullahi — Bioresource Development Unit, National Biotechnology Research And Development Agency, Abuja

The increasing demand for sustainable materials has intensified research into lignin-based adhesives derived from agricultural biomass. This study presents an integrated approach for optimizing organosolv extraction of lignin from groundnut shell. A three-factor central composite design (CCD) of the response surface method (RSM) was applied to optimize extraction variables using Design-Expert 13.0.1, including ethanol concentration, temperature, and reaction time, considering % yield and lignin reactivity index (LRI). The model was tested with its adequacy fit statistics, where the R2 value is 0.9941 which has 0.90 % and 4.4 % difference from the adjusted R2 and predicted R2 values. The theoretical optimal parameters obtained were 55 % ethanol concentration, 120 ℃ temperature, and 45 minutes reaction time, which yielded a lignin recovery of 61.13 % and 5.17 LRI. These were validated, with close values of the responses: 60.24% yield and 5.25 LRI, having a 1.45 % and 1.52 % error for yield and LRI, respectively, as compared with the theoretical values. FTIR and compositional analysis confirmed successful isolation of a lignin-rich fraction from groundnut shell. The extracted lignin retained characteristic hydroxyl, aliphatic C-H, aromatic skeletal, and C-O/ether functionalities, with prominent absorptions observed around 3404, 2928, 1508 – 1529, 1410 – 1412, and 1044 – 1119 cm-1. The novelty of this work lies in the consideration of the quantity and quality of lignin in the optimization of the organosolv extraction method of groundnut shell lignin, an underutilized agricultural waste, to produce a functionally improved adhesive precursor. Conclusively, the optimized extraction conditions produced high lignin yield and enhanced lignin reactivity, demonstrating that groundnut shell is a sustainable and promising source of reactive lignin for the development of bio-based adhesive precursors. These findings provide a reliable foundation for the subsequent modification and functionalization of high-performance and environmentally friendly bio-adhesive synthesis.

Keywords Lignin Organosolv Lignin Reactivity Index Central Composite Design Groundnut Shell Adhesive Precursor

Palm Fruit Bunch Ash as a Partial Cement Replacement in Sandcrete Block

Elijah Adaofoyi Adache — Federal University Of Technology Minna

Theophilus Yisa Tsado — Federal University Of Technology Minna

James Olayemi James — Federal University Of Technology Minna

This empirical study investigates the potential of Oil Palm Empty Fruit Bunch Ash (PFBA) as a partial cementitious replacement in sandcrete block production. The material was produced via a systematic pre-burning process to convert empty fruit bunches into charcoal, followed by controlled calcination to obtain reactive pozzolanic ash. Physical characterization, including specific gravity and fineness (sieve size 45µm), was conducted per BS 1377:1990 and EN 196-6 standards. Mechanical performance was evaluated by substituting Ordinary Portland Cement (OPC) with PFBA at 0%, 5%, 10%, 15%, and 20% levels. Results indicate that while strength development is sustained over a 28-day curing period, increasing PFBA content correlates with reduced compressive strength and density, alongside increased water absorption. The study identifies 10% as the optimal replacement threshold, achieving a 28-day compressive strength of 3.51 N/mm², which complies with the minimum requirements of the Nigerian Industrial Standard (NIS 978:2017). Furthermore, the research evaluates technical risks related to chloride content, environmental benefits of a low-emission approach, and the economic viability of controlled incineration. The findings conclude that with rigorous quality control and chemical pre-treatment, PFBA offers a sustainable, eco-friendly solution for masonry production in the Nigerian construction industry.

Keywords Sustainable construction Oil Palm Empty Fruit Bunch Sandcrete blocks Cement replacement Material characterization.

PHYSICO-MECHANICAL PROPERTIES OF SUSTAINABLE TERNARY BLENDED CONCRETE INCORPORATING CORN COB ASH AND RICE HUSK ASH AS PARTIAL CEMENT REPLACEMENTS

Williams Ejembi — Ahmadu Bello University

Prof. Y. D. Amartey — Ahmadu Bello University

Prof. Adamu Lawan — Ahmadu Bello University

Bilkisu Amartey — Ahmadu Bello University

Engr. Joseph Kevin Zambwa — Ahmadu Bello University

Raphael Ejembi — Ahmadu Bello University

This study evaluated the physico-mechanical properties of sustainable ternary blended concrete incorporating corn cob ash (CCA) and rice husk ash (RHA) as partial cement replacements. The work assessed the suitability of these agricultural by-products as supplementary cementitious materials (SCMs) for sustainable concrete production. Laboratory investigations were carried out on RHA and CCA in accordance with British Standards (BS EN) and ASTM procedures to ensure reliable and accurate results. Physical characterization demonstrated compliance with standard requirements, including a cement soundness of 1.0mm. The cement exhibited a fineness of 97.7%. Aggregate tests, including specific gravity and particle-size grading, also met relevant standards for quality concrete production. Following the procedures and requirements of ASTM C618:2023, RHA was classified as a Class F pozzolan, with a combined SiO₂, Al₂O₃, and Fe₂O₃ of 81.33%, while CCA had 64.85%, making it a Class C pozzolan. X-ray fluorescence (XRF) and X-ray diffraction (XRD) identified amorphous silica and other reactive phases in both ashes, confirming their pozzolanic reactivity and ability to participate in cement hydration, thereby enhancing concrete strength and durability. The reference Grade 25 concrete (Control) has the following strength margins of 22.1N/mm2, 25.3N/mm2, 28.0N/mm2 and 32.1N/mm2 for 7, 28, 56, and 90 days, respectively. In ternary-blended concrete, cement was replaced with 5% CCA and 10% RHA, yielding an optimum mix with compressive strengths of 25.5N/mm2, 37.0N/mm2, 39.5N/mm2, and 41.5N/mm2 at 7, 28, 56, and 90 days, respectively. These results showed increases of 15.4%, 46.3%, 41.1%, and 29.3% in the sustainable ternary blended concrete over the referenced concrete at the 7, 28, 56, and 90-day curing periods. The findings demonstrate that CCA and RHA are viable SCMs that reduce cement consumption, lower carbon emissions, promote effective waste management, and support environmentally sustainable concrete production without compromising material quality in practical construction applications and long-term infrastructure development.

Keywords Corn Cob Ash Rice Husk Ash Pozzolanic Materials Sustainable Concrete Physico-Mechanical Properties Ternary Blends

Preparation of a Porous Waste Expanded Polystyrene/Bamboo Fibre Nanocomposite Material for CO2 Capture

Aliyu Ibrahim Isah — Kaduna Polytechnic Kaduna

Ibrahim Ibrahim Abdulwahab — Kaduna Polytechnic

Nanoporous materials have become some of the most dynamic and rapidly evolving materials for carbon dioxide (CO2) capture. This study focused on the preparation of nanocomposites from bamboo fibres nanopowder (BFNP) and waste expanded polystyrene (WEPS) for CO2 capture. The bamboo fibres were chemically treated using Sodium Hydroxide (NaOH) in order to remove lignin, pectin and other impurities and also to improve the adhesive tendency with the polymer matrix. The effect of NaOH treatment on surface morphology and crystallinity properties of bamboo fibres were investigated using Fourier Transform Infrared (FTIR), Scanning electron microscopy/Energy dispersive X-ray spectroscopy (SEM/EDS) and X-ray Diffraction (XRD). Box-Behnken Design (BBD) of the Response Surface Methodology (RSM) was used to establish design matrix, optimize mixing conditions. The optimization of mixing parameters predicts solution for bamboo fibre loading of 35.9 wt%, mixing time of 3.9 min and mixing temperature of 25.7. The nanocomposites were prepared using Lay-up technique and their properties were then investigated using FTIR, XRD, SEM, and Brunauer-Emmett-Teller (BET). The textural properties of the nanocomposite showed a BET surface area of 847.6m2/g and an average pore diameter of 1.85m3/g which indicates that the material is porous and falls within the standard pore size for CO2 adsorption, mesopores favours large molecules adsorption while micropores favour small molecules adsorption.
Keywords: Carbon capture; bamboo fibre; west expanded polystyrene; nanocomposites; CO2 adsorption

Keywords Carbon Capture Bamboo Fibre Waste Expanded Polystyrene Nanocomposites CO2 adsorption

PROBABILISTIC RELIABILITY ANALYSIS OF REINFORCED METAKAOLIN-BASED GEOPOLYMER CONCRETE BEAMS SUBJECTED TO VARIATIONS IN GEOPOLYMER MIX PARAMETERS

Ibrahim Aliyu — Ahmadu Bello University, Zaria

Idayat Oluwakemi Sholadoye — Department Of Civil Engineering, Ahmadu Bello University, Zaria

J. M. Kaura — Department Of Civil Engineering, Ahmadu Bello University, Zaria

Abubakar Abbas Aliyu — Bankanu And Partners Limited, Suite 001, Basement Level, Mortgage House, C.b.d Abuja

Jamilu Yau — Department Of Building. A.t.b.u. Bauchi

The study investigated the probabilistic effect of NaOH Molarity (Mc), Na2SiO3:NaOH (ALr), and alkaline-liquid:Metakaolin (ALm), on the reliability of metakaolin-based geopolymer concrete beams reinforced with two (2) 8 mm bars as tension reinforcement under a failure load of 39 kN. The assessment was performed using the First Order Reliability Method (FORM). Compressive strength models were developed for the investigated variables, which were incorporated into the failure modes limit-state equations through the FORM5 package to evaluate the beam’s reliability. The probabilistic analyses were conducted by varying Mc (6-16 M), ALr (0.5-2.5) and ALm (0.4-1.0). Results from the analyses showed that the models explained 63.4% and 93.2% of the compressive strength variations, respectively, for Mo/ALr and ALm/Wc. Additionally, increasing Mc from 6 M to 10 M improved the reliability of the Reinforced Metakaolin Based Geopolymer concrete (RMBGC), whereas further increase to 12 M and beyond reduced reliability. Increasing ALr from 0.5 to 2.5 and ALm from 0.4 to 1.0 consistently enhanced the reliability. Among all variables, ALm exerted the greatest influence, producing the largest improvement in safety index across all failure modes. It was also noted that the Moment failure mode was most sensitive to mix-parameter variations, followed by shear, while deflection was least affected. In general, the study demonstrates that optimising ALm, ALr, and Mo (approximately 10 M) provides the greatest improvement in the reliability and structural safety of metakaolin-based geopolymer reinforced concrete beams.

Keywords Reinforced Metakaolin-Based Geopolymer concrete First-Order Reliability Method (FORM) Safety index Mix design parameters

Silica-Based Matrices for Microbial Cell Encapsulation and Immobilization: A review

Utibeabasi Okonbaba — Ahmadu Bello University, Zaria

H. I. Atta — Ahmadu Bello University, Zaria

Abdulazeez Yusuf Atta — Ahmadu Bello University, Zaria

Baba Jibril El-yakubu — Ahmadu Bello University, Zaria

Microbial cell immobilisation confers protection, reusability, and enhanced tolerance to toxic and fluctuating environments, and is increasingly applied in bioremediation, biocatalysis, and fermentation. Among the available carriers, silica and silica-hybrid matrices are attractive for their mechanical strength, chemical and thermal stability, biocompatibility, and shielding of cells from ultraviolet light and heavy-metal ions. This review examines silica-based precursors and matrices for microbial encapsulation, spanning sol–gel silicas (tetraethyl and tetramethyl orthosilicate, and the water-miscible THEOS), aminosilane (APTES) coatings applied layer-by-layer to alginate beads, silica–alginate hybrids, silica–poly(ethylene glycol) composites, and low-cost biosilica recovered from agro-industrial residues such as rice husk ash and sugarcane bagasse ash. Reported systems are compared by precursor purity, microbial compatibility, and the resulting encapsulation efficiency, cell viability, and mechanical stability. A recurring theme is the trade-off between porosity and stability: high porosity eases the diffusion of substrates and products. Still, it weakens the capsule, whereas dense matrices protect cells at the expense of mass transport, so that pore-forming additives are used to tune this balance. Biosilica precursors additionally offer low cost, antimicrobial character, and circular-economy benefits, though feedstock variability and purification remain limitations. The review concludes that silica matrices, particularly porosity-engineered silica–alginate systems, are well suited to encapsulating hydrocarbon-degrading microorganisms for the treatment of petroleum refinery effluent, and identifies controlling diffusivity, mechanical stability, and scale-up as the principal challenges to wider application

Keywords microbial encapsulation silica-alginate matrices cell immobilization sol-gel silica hydrocarbon biodegradation.

The Use of Green Materials for Building Construction: A study of the Nigerian Construction Industry.

Alhassan Galadima — Ahmadu Bello University Zaria

Umar Ibrahim Kwami — Ahmadu Bello University Zaria

Muazu Bello — Ahmadu Bello University

The construction industry remains a major contributor to global carbon emissions, resource depletion, and energy consumption, with traditional materials such as cement and steel carrying high environmental costs. Green materials derived from renewable, recycled, or low-impact sources offer a sustainable alternative to conventional building practices. This study examines the current state of green materials adoption in the Nigerian construction industry through a mixed-methods approach that combines literature synthesis with a questionnaire survey of construction firms operating in Kaduna, Plateau, and the Federal Capital Territory, Abuja. The research assesses awareness levels, identifies barriers to adoption, and evaluates the extent to which green building principles are integrated into current practices. Findings reveal that while green materials demonstrate significant potential to reduce embodied energy and carbon footprint—with hempcrete and bamboo composites providing excellent insulation and renewability, recycled aggregates and fly ash reducing reliance on virgin cement, and mycelium-based blocks showing promise in biodegradability—adoption in Nigeria remains critically low. Only 29.6% of respondents confirmed that green materials principles are being considered by construction firms, and 66.7% indicated that the Nigerian building industry is not progressing toward green building construction. Key barriers include inadequate awareness and education (33.3% of respondents), lack of standardised materials and technology (48.1%), absence of regulatory enforcement, high initial costs, limited large-scale production, and regulatory gaps in certification. The study concludes that achieving sustainable construction in Nigeria requires increased professional education, mandatory site waste management, strengthened regulatory frameworks, financial incentives, and enhanced cooperation among stakeholders. The findings contribute to the growing body of knowledge on sustainable construction practices in developing economies and offer practical recommendations for policymakers and industry practitioners.

Keywords Green Building Materials Sustainable construction Bio-based Composites Recycled construction materials Nigerian construction industry Low-carbon building technologies.

THERMAL EVALUATION OF ASPHALT CONCRETE FOR PAVEMENT-BASED THERMOELECTRIC ENERGY GENERATION: INFLUENCE OF AGGREGATE TYPE AND GRADATION

Sadiq Muktar Muhammad — Bayero University, Kano

Aminu Suleiman — Bayero University, Kano

Asphalt pavements absorb large amounts of solar radiation and develop pronounced through-thickness temperature gradients that thermoelectric generators (TEGs) can, in principle, convert into electricity. The magnitude of the recoverable heat depends on the thermal properties of the asphalt concrete, which are in turn governed by mixture composition. This study evaluates the mechanical and thermal behaviour of asphalt concrete for pavement thermoelectric energy harvesting and examines the influence of aggregate type and gradation. Four mixtures were produced from basalt and granite aggregates in wearing-course (WC) and binder-course (BC) gradations: BWC, BBC, GWC and GBC. Marshall mix design (ASTM D6927) established optimum bitumen contents of 5.0–5.5%. Mechanical performance was assessed through Marshall stability, flow and indirect tensile strength (ITS) tests; the apparent thermal conductivity (kapp) and specific heat capacity were measured using a steady-state electrical (Searle-type) apparatus. A three-dimensional transient heat-transfer model was built in Abaqus to compare the relative thermal response of the mixtures. Basalt mixtures gave the highest stability (BBC = 7.83 kN) and ITS (BBC = 493 kPa). The measured kapp values (2.90–4.03 W/m·K) lie above the range normally reported for asphalt concrete and are treated here as relative, comparative indicators rather than absolute material constants. Within this comparative framing, GWC exhibited the highest apparent conductivity and the largest simulated heat flux (2371 W/m²), indicating the greatest thermal-harvesting potential among the mixtures studied. The finite-element results were internally consistent with the analytical Fourier solution to within 13%. Aggregate type and gradation significantly influenced both mechanical and thermal behaviour, providing guidance for material selection in TEG-integrated pavements.

Keywords Asphalt concrete thermoelectric generators energy harvesting apparent thermal conductivity aggregate type

Tribological Behaviour and Multi-Objective Optimization of Austempered High Carbon Steel Using Sulfate Salt-Modified Sesame Oil

Hafiz Bashir Aminu — Ahmadu Bello University Zaria & Federal Polytechnic Idah Kogi State

Rayyan Mamuda Dodo — Ahmadu Bello University, Zaria

Terver Ause — Ahmadu Bello University, Zaria

This study investigates the tribological behaviour and multi-response optimization of austempered high-carbon steel processed using sulfate salt-modified sesame oil as a bio-based quenching medium. Potassium sulfate (K₂SO₄) and sodium sulfate (Na₂SO₄) concentrations, austempering time and temperature were varied using a Taguchi L9 orthogonal array. Wear rate and coefficient of friction (CoF) were evaluated under dry sliding conditions, while scanning electron microscopy (SEM) was used for qualitative microstructural examination. Grey Relational Analysis (GRA) was employed to simultaneously optimize the two smaller-the-better responses. The nine experimental runs produced wear rates of 0.0003 – 0.0036 mm³/Nm and CoF values of 0.048 – 0.118. Run 4, corresponding to 1.5% K₂SO₄, 0% Na₂SO₄, 45 min and 320 °C, produced the highest experimentally observed GRG of 0.8519. The Taguchi response-mean analysis predicted a combined optimum of 3% K₂SO₄, 0% Na₂SO₄, 45 min and 320 °C, with an estimated GRG of 0.8721. However, this predicted condition was not included in the L9 matrix and therefore remains experimentally unverified. Pooled ANOVA indicated that austempering temperature contributed 47.74% to GRG variation, followed by Na₂SO₄ concentration at 19.92%, although neither retained factor was statistically significant at the 5% level. SEM observations suggested associations between comparatively refined transformation morphologies and favourable tribological responses, but definitive phase identification requires complementary XRD or EBSD analysis. The findings demonstrate the potential of sulfate salt-modified sesame oil for tailoring the combined wear and friction response of austempered high-carbon steel.

Keywords Austempering Sesame oil Sulfate salts Tribology Grey Relational Analysis

DEVELOPMENT OF A NARROW BAND INTERNET OF THINGS (NB-IOT) MONITORING AND CONTROL MODEL FOR URBAN DRAINAGE SYSTEM IN KANO, NIGERIA

Abba Abdulhadi — Abubakar Tafawa Balewa University Bauchi

Dr Hassan Sabo Miya — Abubakar Tafawa Balewa University Bauchi

Usman A. Umar — Abubakar Tafawa Balewa University Bauchi

Urban flooding in Kano, Nigeria, poses significant socio-economic and infrastructural challenges, largely exacerbated by a lack of continuous, real-time drainage monitoring. This thesis presents the development, implementation, and evaluation of a Narrow Band Internet of Things (NB-IoT) monitoring and control model designed specifically for urban drainage systems. The proposed architecture integrates ultrasonic water level, Doppler flow, and rainfall sensors with a low-power microcontroller utilizing LTE Cat NB1 connectivity. Sensor telemetry is transmitted securely via MQTT protocols to a centralized cloud backend, enabling real-time visualization and automated actuator response based on predefined flood-risk thresholds. To empirically validate the system, a 28-day pilot deployment was executed across three critical drainage points in Kano: Sabon Gari, Bompai, and the City Center. The evaluation demonstrated exceptional reliability in subterranean environments, achieving an average packet delivery success rate exceeding 95% and an end-to-end latency of roughly 3.17 seconds. The study concludes that the developed NB-IoT model provides a robust, scalable, and energy-autonomous blueprint for transitioning Kano toward proactive, data-driven flood management.

Keywords AI IOT

DEVELOPMENT OF A Q-LEARNING-DRIVEN INTERFERENCE MANAGEMENT MODEL WITHIN THE ADAPTIVE RRM FRAMEWORK FOR ADAPTIVE TRANSMIT POWER OPTIMIZATION

Abubakar Abdulkadir — Ahmadu Bello University, Zaria

H. A. Abdulkareem — Ahmadu Bello University, Zaria

Z. M. Abdullahi — Ahmadu Bello University, Zaria

Elvis Obi — Ahmadu Bello University Zaria

Aliyu Umar Abubakar — Ahmadu Bello University, Zaria

Abstract— The rapid densification of fifth-generation (5G) heterogeneous networks has improved network capacity and coverage but also increased co-tier and cross-tier interference. In ultra-dense multi-tier Het-HetNets, traditional static and semi-static radio resource management techniques are insufficient to address rapidly changing interference, traffic demands, and user distribution. This paper presents a Q-learning-driven interference management model within an adaptive Radio Resource Management (RRM) framework to dynamically optimize transmit power for PeNBs. The hybrid Q-learning power allocation framework models each PeNB as an autonomous reinforcement-learning agent that observes network conditions, selects transmit power actions, receives performance-based rewards, and updates its Q-table using the Bellman learning mechanism. Key factors such as network capacity, interference, transmit power consumption, and Quality of Service (QoS) are incorporated into the learning process. A 5G Het-HetNet simulation in MATLAB, featuring one MeNB, one gNB, sixteen PeNBs, and diverse user equipment, evaluates three communication scenarios with different interference and spectrum-sharing conditions. The Q-learning process demonstrates stable convergence within 80,000 iterations. Results show an average improvement of 3.37% in 5G user equipment (5G-UE) capacity and 14.81% in the minimum capacity of small-cell users compared to the benchmark model by Iqbal et al. Additionally, the proposed approach maintains 5G-UE capacity above the QoS threshold under the tested conditions, highlighting its effectiveness in interference management and RRM in ultra-dense 5G networks.

Keywords 5G and B5G Het-HetNets Q-learning interference management power allocation adaptive RRM.

Improved Clustering Approach for Hotspot Mitigation in Wireless Sensor Networks Using Load-Aware Cluster Head Selection

Samson Bitrus Visa — Ahmadu Bello University, Zaria

Abdulqadir Mahmudu Jada — Department Of Electrical And Electronics Engineering Technology, Adamawa State Polytechnic, Yola, Nigeria

Aliyu Muhammad Isa — Department Of Electrical And Electronics Engineering Nigerian Biu Borno State

Yohanna Ali Mshelia — Department Of Electronics And Telecommunications Engineering, Ahmadu Bello University, Zaria, Nigerian

Okehie M. Baslem — Department Of Engineering And Space System National Space Research And Development Agency (nasrda), Abuja, Nigeria

Adamu Muhammad — Department Of Electrical And Electronics Engineering, Federal Polytechnic, Daura, Nigeria

Wireless Sensor Networks (WSNs) are susceptible to hotspot formation caused by uneven traffic distribution and excessive forwarding responsibilities on selected sensor nodes. This paper presents an Improved Clustering Approach to Mitigate Hotspots (ICAMHS), developed as an enhancement of the Cluster-Based Genetic Routing Protocol (CGRP). ICAMHS integrates K-means clustering, energy- and distance-aware cluster-head selection, traffic-load consideration, an improved routing fitness function, and fault-tolerant route recovery. The proposed approach was evaluated against CGRP using two performance metrics: decoding probability for a 1000-node network and end-to-end latency. At a decoding rate of 3.0, ICAMHS achieved a decoding probability of 1.00, compared with 0.98 for CGRP. These correspond to relative improvements of 2.04%. For latency, ICAMHS consistently produced slightly lower values than CGRP, achieving 998 ms at 1000 nodes compared with 1000 ms, representing a 0.20% reduction. The results indicate that ICAMHS improves decoding performance while maintaining comparable latency, demonstrating its potential for reliable communication in large-scale WSNs.

Keywords Wireless Sensor Networks hotspot mitigation ICAMHS CGRP clustering cluster-head selection.

INTERFERENCE MITIGATION OF UNDERLAY SECONDARY USERS USING INTERFERENCE ALIGNMENT

Isiyaku Yau — Ahmadu Bello University, Zaria

Mohammed Dikko Amustapha — Department Of Electronics And Telecommunications Engineering Ahmadu Bello University, Zaria

Shamsuddeen Abdullahi Mika’il — Department Of Electronics And Telecommunications Engineering Ahmadu Bello University, Zaria

Joshua David — Department Of Electrical/electronics Engineering Kogi State Polytechnic Lokoja

Usman Yau — Department Of Electronics And Telecommunications Engineering Ahmadu Bello University, Zaria

Nafiu Murtala Kamaluddeen — Department Of Electronics And Telecommunications Engineering Ahmadu Bello University, Zaria

As the number of wireless devices and services grows exponentially, the Radio Frequency (RF) spectrum is becoming an increasingly scarce resource. Again, the current fixed spectrum-licensing policy has made the RF spectrum underutilized. Cognitive Radio (CR) seeks to provide a solution to address the imbalance between spectrum scarcity and spectrum underutilisation by allowing cognitive users, called Secondary Users (SUs), to share the spectrum with the licensed users called Primary Users (PUs) in a manner that the PUs do not suffer harmful interference. The work is aimed at mitigating undelay cognitive intra-network interference with a view to enhancing the effective sum capacity of the SUs. The PU is protected through the interference temperature (IT) model. Ergodic Interference Alignment (IA) scheme under the IT constraints is developed for mitigating the mutual interference among the SUs. To provide a benchmark to gauge the performance of the developed model, the sum capacity through the time-division scheme is first obtained. A closed-form expression for the sum capacity of a three-user underlay cognitive channel is derived. Applying the ergodic IA with IT constraints enhances the sum capacity of the SUs, thereby achieving 23.54% and 24.77% gains in the channel sum capacity under maximum and average IT limits, respectively. This gain is with respect to the time-division scheme at a signal-to-noise ratio of 19dB. By utilizing the long delay time associated with ergodic IA to send more bits in the time-division scheme, 3.0094 bps/Hz and 3.1741 bps/Hz gains in spectral efficiency were achieved under maximum and average IT limits over a full time-division scheme at an SNR of 19dB.

Keywords Cognitive Radio Interference Alignment Underlay Spectral Efficiency SNR

Time of Arrival–Received Signal Strength Localization in Non-Line-of-Sight Environments Using Huber Loss Enhanced Second-Order Cone Programming

Isaac Hyeltiuda Charles — Department Of Electronics And Telecommunications Engineering, Ahmadu Bello University, Zaria.

Abdulmalik Shehu Yaro — Department Of Electronics And Telecommunications Engineering, Ahmadu Bello University, Zaria.

Shamsuddeen Abdullahi Mikail — Department Of Electronics And Telecommunications Engineering, Ahmadu Bello University, Zaria.

Isiyaku Yau — Department Of Electronics And Telecommunications Engineering, Ahmadu Bello University, Zaria.

Mohammed Dikko Amustapha — Department Of Electronics And Telecommunications Engineering, Ahmadu Bello University, Zaria.

Yohanna Ali Mshelia — Department Of Electronics And Telecommunications Engineering, Ahmadu Bello University, Zaria.

Accurate wireless localisation in Non-Line-of-Sight (NLOS) environments remains challenging because multipath propagation, signal blockage, and environmental obstructions introduce severe measurement errors. Conventional Least Squares (LS) estimators are particularly vulnerable to NLOS-induced outliers because their quadratic loss function assigns disproportionately large weights to large residuals. This study proposes a robust hybrid Time of Arrival-Received Signal Strength (TOA-RSS) localisation framework that combines Second-Order Cone Programming (SOCP) with the Huber loss function to mitigate the influence of NLOS-corrupted measurements. The nonconvex Euclidean-distance localisation problem is transformed into a convex SOCP formulation through epigraph reformulation, while the piecewise-convex Huber penalty limits the contribution of large residuals. Monte Carlo simulations covering a comprehensive range of LOS/NLOS anchor configurations demonstrate the effectiveness of the proposed estimator. Under the most severe scenario, involving 0 LOS and 10 NLOS anchors, SOCP+Huber reduced position RMSE by up to 43.4% compared with conventional LS and 23.1% compared with non-robust SOCP. Cumulative distribution analysis further showed that 75–78% of localisation estimates were within 5 m of the true position, compared with approximately 70% for LS. The improvement was most pronounced under severe NLOS conditions, while performance remained competitive under LOS-dominant scenarios, confirming effective outlier suppression. The robustness was achieved with a modest computational increase, from O(n³·⁵) for standard SOCP to O(n⁴), remaining substantially lower than the O(n⁶) complexity associated with semidefinite-programming alternatives.

Keywords Wireless localization TOA/RSS NLOS mitigation second-order cone programming Huber loss

Advanced Manufacturing, Materials and Sustainable Production

Advancing Sustainable Fructose Syrup Production from Sweet Sorghum

Biodegradable Structure-Directing Agents for Sustainable Synthesis of ZSM-5 Zeolite: A Review of Amino-Acid and Biopolymers Routes

Comparative Study of Thermal, Zeolite-Y Catalytic and Ni-Doped Zeolite-Y Catalytic Cracking of Gas Condensate

Density Functional Theory Investigation of Methane Steam Reforming on Ni(111) and Pd1–Cu(111) Single-Atom Alloy Surfaces

Determination of Low-Temperature Low-Pressure (LTLP) Filtration Properties of Drilling Mud Formulated from Arawa Bentonite Clay for Oil and Gas Drilling Application

Development and Microstructural Characterization of Al-Si-Mg / Giro Clay Nanoparticle Composites Fabricated via Stir Casting for Marine Applications

Effect of Double Pressing and Double Sintering on the Mechanical and Tribological Properties of Aluminium Matrix Reinforced Rice Husk Ash Composites

EFFECT OF HEAT TREATMENT AND QUENCHING MEDIA ON THE MECHANICAL TRIBOLOGICAL THERMAL AND MICROSTRUCTURAL BEHAVIOUR OF A6082-SNSA/MWCNT HYBRID COMPOSITES

EVALUATION OF DIFFERENT COMPUTATIONAL STRATEGIES FOR THE FORMULATION OF IONIC LIQUIDS FOR SUGAR SOLUBILITY APPLICATION

Geospatial Assessment of Soil Textural Classes and the Implications on Achieving SDG 2 in Northwest Nigeria

Investigation into the Use of Locally Available Materials for the Production of Investment Casting Mould

Mechanical, Optical and Engineering Assessment of Polypropylene/Fiberglass Composites for Translucent LPG Cylinder Applications

Performance Evaluation of Lateritic Adobe Bricks Stabilized with Granite Powder: Strength, Durability, and Thermal Resilience

Production of Silica from Agricultural Wastes for Application in FCC/RFCC Catalyst Development: A Mini Review

Sugarcane Bagasse Ash as a Sustainable Silica Precursor for Zeolite Synthesis: A Review of Extraction Routes

Emerging Technologies and Digital Transformation in Engineering Education and Practice

An Edge AI-Driven Cyber-Physical Framework for Green Network Optimization and Resilient Infrastructure in Emerging Economies

ARTIFICIAL INTELLIGENCE BASED SECURITY FRAMEWORK FOR WIRELESS INTERNET OF THINGS COMMUNICATION FOR DEVICES WITH HETEROGENEOUS ARCHITECTURE

COMPUTATIONAL INVESTIGATION OF ACTIVE PALM OIL COMPONENTS AS ECO-FRIENDLY CORROSION INHIBITORS FOR COPPER METALS

DEVELOPMENT OF A HYBRID SUPPORT VECTOR MACHINE AND BAT OPTIMIZATION ALGORITHM FOR ENHANCED SPECTRUM SENSING IN TELEVISION WHITE SPACE NETWORKS

Factors Influencing the Adoption of Mixed Reality Technology for Construction Projects Cost Estimation

Intelligent Energy Management in Agriculture: A Systematic Review of Internet of Thing, Renewable Integration, and Artificial Intelligence Techniques

Measurement of Liquid Film Height in Gas-Liquid Two-Phase Flows Using Twin-Wire Conductance Probes

Student Verification Assistant: A Low-Cost Multimodal Biometric System for Secure Examination Identity Authentication

Emerging Technologies for Safe Engineering Practices and Environmental Protection

Application of Artificial Intelligence in Transportation Safety and Environmental Administration: A Systematic Review

ASSESSING THE IMPACT OF CLIMATE CHANGE ON GROUNDWATER RECHARGE POTENTIAL IN PALLADAN, ZARIA, KADUNA STATE, NIGERIA.

Assessment of Electrical Power Quality Issues in Aircraft Dc System: Analysis of Voltage Drop and Harmonic Distortion

California bearing ratio of geopolymer-stabilized lateritic soil using sugarcane bagasse ash and rice husk ash as precursors

Climate-Resilient Infrastructure Design for Flood-Prone Nigerian Cities: A Case Study of Maiduguri, Borno State.

COMPARATIVE ASSESSMENT OF PAVEMENT DISTRESS USING CONVENTIONAL MEASUREMENTS AND UAV PHOTOGRAMMETRY ALONG THE GOMBE - KWAMI HIGHWAY, NIGERIA

Container - Water Interaction: Modeling Physicochemical and Microbial Changes During 14 Day Storage in Clay and Plastic Containers

Deep Learning Prediction of Remaining Useful Life for Turbofan Engine using Attention Augmented LSTM Based Network

Design and Performance Evaluation of a Dual-Media Filtration System Using Palm Kernel Shell Activated Carbon for Wastewater Treatment

Design Optimisation and Impact Assessment of a Biogas-Integrated Anaerobic Baffled Reactor Wastewater Treatment System at Ikoyi Correctional Centre, Lagos, Nigeria

Designing Enforcement for Safety, Not Hazard: Evidence from a Traffic Management System Failure in Kano Metropolis

DEVELOPMENT AND PERFORMANCE EVALUATION OF A WASTE PLASTIC SHREDDER

Development of an optimal Load Frequency Control strategy of the two-area power systems using Arithmetic Optimization Algorithm

Effect of Base-seal on cement -Stabilized clayey Soil Admix with Rice Husk Ash (R.H.A)

EFFECT OF MUNICIPAL SOLID WASTE LEACHATE ON PLASTICITY CHARACTERISTICS OF CLAY SOIL

Effects of hydrocarbon impurities on concrete strength and Durability: A comprehensive review.

Emerging Technologies for Safe Engineering Practices and Environmental Protection: A Systematically Informed, Evidence-Graded Review with a Proposed Nigerian Adoption Framework

Enhanced Anaerobic Digestion of Cow Dung and Poultry Dung Via a Coupled Microbial Electrolytic Cell: Optimization, Kinetics, and Thermodynamic Studies.

Flood Inundation Risk Assessment of An Earthen Dam Under Piping Failure Using HEC-RAS And QGIS: A Case Study of Kubanni Dam Zaria, Nigeria.

Geo-spatial 2D analysis of Anthropogenic Heavy Metal Sources and Distribution in Soil and Groundwater In Funtua, Katsina State

Hydrodynamic Assessment of Piping-Induced Dam-Break and Downstream Flood Hazard Classification at Zobe Dam, Nigeria. An integrated HEC-HMS and HEC-RAS Modeling Approach

IINFLUENCE OF SLICE THICKNESS AND DRYING TEMPERATURE ON THE PROXIMATE COMPOSITION OKRA: IMPLICATIONS FOR NUTRITIONAL QUALITY AND DRYING PROCESS OPTIMIZATION

IMPACT OF AGEING WATER INFRASTRUCTURE ON WATER SUPPLY IN NIGER STATE:CASE STUDY OF SULEJA AND MINNA

IMPACTS OF ROAD CONSTRUCTION SITE ACTIVITIES ON THE OCCURRENCE OF ACCIDENTS: A CASE STUDY OF THE ZARIA–KADUNA ROAD

Infrastructure Characterization and Physical Integrity Assessment of Urban Water Distribution Systems: A Risk-Based Framework for Sustainable Asset Management in Minna, Nigeria

INTEGRATED EXERGETIC–ECONOMIC ASSESSMENT OF THERMAL AND CATALYTIC PYROLYSIS OF HOUSEHOLD THERMOPLASTIC WASTE FOR SUSTAINABLE WASTE-TO-ENERGY APPLICATIONS

MINIMIZATION OF POWER LOSSES IN DISTRIBUTION NETWORKS THROUGH SMART GRID TECHNOLOGIES: A CASE STUDY OF BWARI 33 KV DISTRIBUTION NETWORK

Multivariate and Machine Learning-Based Assessment of Pore Pressure Dynamics for Dam Safety Monitoring: A Case Study of Gurara Dam, Nigeria

Non-Parametric Assessment of Wind-Sector and Elevation Effects on Contaminant Distribution around a Cement Factory

Optical Emission Spectroscopy (OES) Analysis of Corrosion of High-Grade Conventional 5 mm Ukrainian Metallic Plate Used in Tanker Truck Fabrication in Nigeria

Performance Evaluation of Model Reference Adaptive Control for String Stability in Heavy-Duty Truck Platooning

Probabilistic Frequency Estimation of Boiling Liquid Expanding Vapour Explosion in a Liquefied Petroleum Gas Add-On Skid System Using Integrated Fault Tree and Event Tree Analysis

Process Intensification of a 50 BPD Modular Mini-Refinery : A Simulation-Driven Pinch Analysis Approach for Enhanced Heat Recovery and Sustainable Refining in Nigeria.

Spatial Variation Assessment of Groundwater Quality in Iwo Local Government Area, Osun State, Nigeria.

Study of the Corrosion Rate of Nigerian High-Grade Conventional 5 mm Ukrainian Metallic Plate Using Weight Loss (Gravimetric) Method

Engineering Innovations, Technology Commercialisation and Industrial Policy

A comprehensive review on the poultry brooding requirements and forced air methods of heat generation for brooding.

Bioelectricity Generation and Nutrient Removal from Landfill Leachate Using Double-Chamber Microbial Fuel Cells

Comparative CFD Analysis of Rib Architectures and Honeycomb Surfaces for Brake Drum Cooling

Conceptual Design, Operations, and Theoretical Modeling of a 1 kW Physical Scale Prototype for the Kainji Hydropower Dam

CPS-Driven Adaptive Coordination Framework for Heterogeneous Wireless Sensor Networks in Dynamic and Uncertain Environments

DESIGN AND FABRICATION OF A 5 BSPD PILOT-SCALE SEMI-REGENERATIVE CATALYTIC NAPHTHA REFORMING UNIT

Desirability-Based Multi-Response Optimization of Flexural Performance in Bamboo and Steel Reinforced Concrete Beams

Energy-Efficient Communication and Routing Strategies in Heterogeneous Wireless Sensor Networks: A Comprehensive Review

Evolution, Prospects, and Future Directions of Nigerian Currency Image Analysis: A Decadal Review.

Feature Selection Using Random Forest Feature Importance for Efficient Network Intrusion Detection on the NSL-KDD Dataset

Physicochemical assessment of hospital waste water through clay membrane composite,a case study of general hospital minna

STRUCTURAL RELIABILITY ASSESSMENT OF REINFORCED CONCRETE BEAM INCORPORATING GROUNDNUT SHELL ASH FOR TILAPIA CONCRETE INCUBATOR

SWOT Analysis of Local Engineering Innovation for Sustainable Industrial Growth in Nigeria: Pathway to SDG Realization

THE EFFECTS OF CONCENTRATED SOLAR IRRADIANCE ON THE OVERALL PERFORMANCE OF MONOCRYSTALLINE AND POLYCRYSTALLINE SOLAR CELLS

Green Mobility and Next Generation Automobile Technologies

CFD-Driven Thermal Analysis and Climate-Adaptive Optimization of Lithium-Ion EV Battery Using Different Cooling Media and Statistical Techniques

Development of a Cyclonic Liquid Spray Scrubber for Emission Control

Investigation of the Physicochemical Properties and Engine Performance Characteristics of Glycine max Biodiesel–Diesel Blends in a Compression Ignition Engine