ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY AND ENVIRONMENT

Interactions Between Varieties, Drying Methods and Packaging Materials on Moisture and Ash Contents of Dried Mango (Mangifera Indica, L) Chips

D. M. Kirawa Abdullahi — 2026-06-02

This study examined the interaction of mango varieties (Keith and Julie), drying methods (open sun, solar cabinet, oven) and packaging materials (glass, plastic, corn starch, polyethylene) on moisture and ash content of dried mango chips over four months period, in order to determine the most effective combination for long term storage and quality. Proximate analysis and statistical analysis using ANOVA with LSD were employed. Key findings indicated that the combination of Keith variety, oven drying, and glass packaging yielded the lowest moisture content (5.00%), enhancing storability and reduced microbial spoilage. For ash content, Keith variety, solar cabinet drying, and glass packaging combination retained the highest percentage (2.44%), indicating better quality preservation. Glass packaging emerged as superior to corn starch, plastic and polyethylene due to its non-porous nature and protective qualities. When compared to plastic, it was observed that, because glass had the least effect on the flavor of food while protecting it from external factors; it preserved flavor better but this was not directly tested in this study. However, when properly sealed, com starch could be an option, due to its light weight, low cost, biodegradability, and eco-friendliness. It is recommended that further research be conducted on the effect of glass packaging on flavor of stored food products. Also, on the proper and improved sealing of corn starch packaging.

Seismic Performance of High-Rise RC Buildings with Square and Circular Columns Using Fluid Viscous Dampers: Time History vs. Pushover Analysis

I. A. David — 2026-06-02

This study presents a comparative evaluation of the seismic performance of high-rise reinforced concrete (RC) buildings with square and circular columns, analysed with and without fluid viscous dampers (FVDs) using nonlinear time history and pushover methods in ETABS 2022. Four structural configurations were investigated: square columns without FVDs (SC), square columns with FVDs (SCFVD), circular columns without FVDs (CC), and circular columns with FVDs (CCFVD), under identical geometric and material properties. Seismic loading was defined in accordance with EN 1998-1, and Imperial Valley-02 ground motion was used for dynamic simulation. Results indicate that, without dampers, circular columns reduced dynamic base shear demand by up to 20% compared to square columns, although exhibiting slightly longer fundamental periods (≈3%). The incorporation of FVDs significantly enhanced seismic performance in both column types; however, circular columns demonstrated superior efficiency. Fundamental time periods were reduced by 24% in SCFVD and 43% in CCFVD, with CCFVD exhibiting a 27% shorter period than SCFVD. Under time history analysis, base shear decreased by 31% in SCFVD and by 44% (X) / 42% (Y) in CCFVD relative to the square-column baseline. However, Pushover analysis showed even greater reductions, reaching 35% in SCFVD and up to 74% in CCFVD. It was clear that Circular column system combined with FVDs provided the most efficient seismic response, achieving the lowest time periods and base shear demands. Thus, the study demonstrate that circular columns enhance the effectiveness of FVDs and offer superior seismic performance compared to square columns in high-rise RC buildings, particularly when evaluated using nonlinear dynamic analysis.

Influence of Reinforcement Ratios on Load and Deflection of Reinforced Geopolymer Concrete Beams

I. Aliyu — 2026-06-02

In recognition of the adverse environmental impacts of the Portland cement manufacturing process, interest has shifted toward developing alternative cementing materials. This shift is also driven by the depletion of fossil fuel reserves, scarcity of raw materials, and the increasing demand for cement and concrete. However, geopolymer cement can serve as a substitute for Portland cement binder in structural concrete. In this research, Reinforced concrete geopolymer concrete beams were produced with metakaolin as the pozzolan. The concrete was produced with a cement made up of metakaolin as the silica and alumina precursor, while Sodium Hydroxide (NaOH) and Sodium Silicate (Na2SiO3) serve as the activator solution. Singly reinforced concrete beams were produced at 1.24%, 1.96% and, 2.86% reinforcement ratios using 8, 10, and 12mm steel reinforcements respectively. The beams were tested according to BS EN 12390-5 (2000). The results showed that the dominant mode of failure of the beams is the diagonal tension shear failure. Additionally, the behavior of the reinforced geopolymer concrete (RGC) beams in deflection was found to be similar to conventional reinforced concrete (RC) beams. Furthermore, the load required for a deflection of 1mm when the reinforcement ratio is 1.24%, 1.96% and, 2.86% is respectively 14kN, 20kN, and 29kN. In addition, a load of 20kN lead to a deflection of 1.33mm, 1.00mm, and 0.65mm for reinforcement ratios of 1.24%, 1.96% and, 2.86% respectively. The maximum deflection at failure of the beam with a 1.24% reinforcement ratio was 3.58mm. The value dropped to 3.01mm and 2.62 mm at 1.96% and 2.86% reinforcement ratios respectively. This showed that similar to conventional concrete, RGC beams with higher reinforcement content have higher stiffness. This therefore showed that deflection assumptions and code recommendations for conventional concrete can be extended to reinforced geopolymer concrete beams (RGCB).

Addressing the Transmission Constraints of Nigeria National Grid via Optimal Distributed Power Flow Controller Placement

O. F. Amakiri — 2026-06-02

The uncertainties in the Nigerian National Grid have raised serious concerns among researchers and stakeholders in the power sector. Aging equipment, inadequate generation, and diminishing transmission capacity cause the persistent instability of the grid, which includes intermittent system collapses and voltage rises or drops that exceed the safe operating limit. After more than a dozen outages in 2025, several have occurred in 2026. Technical issues with 330kV lines and inadequate reserve power frequently cause severe outages, which almost completely stop generation. This study presents a steady state and post-load flow analysis of a 30-bus transmission network in Nigeria in order to evaluate voltage stability using the Modern Voltage Stability Index (MVSI) in MATLAB environment. Preliminary results indicate that twenty-five buses operate within the permissible stability range (0.95-1.05 p.u.), two heavily loaded buses (1.4-1.6 p.u.) exhibit instability of MVSI > 1.05, and three weak buses (MVSI <0.95 at 0.80, 0.89, 0.94). A linear regression model (MVSI = 0.24P + 0.85, R2 = 0.73) indicates that voltage stability is primarily based on loading conditions, with instability hazards rising above 0.83 p.u. To mitigate these issues, a Distributed Power Flow Controller (DPFC) is deployed with a control gain of 0.45 and a maximum reactive power injection of 0.12 MVar per iteration. The proposed approach achieves full system stabilization within 20 iterations, improving the mean MVSI from 0.80 to 0.992 and reduced from 1.6 to 1.002. Post-compensation results show a marginal adjustment in regression performance (R² = 0.68), indicating enhanced system dynamics without altering the intrinsic load–stability relationship. Additionally, voltage profiles at critical buses improve by 3–5%, while power transfer capability increases by approximately 24%. These results demonstrate the effectiveness of DPFC in enhancing voltage stability and transmission efficiency in developing power systems.

Environmental and Performance Assessment of Lithium-Ion and Flow Battery in Hybrid Renewable Energy Systems

G. O. Meyo — 2026-06-02

Reliable and affordable electricity remains critical for rural development in regions where grid expansion is constrained by high costs, difficult terrain, and dispersed settlements. Hybrid Renewable Energy Systems (HRES) that integrate solar, wind, and energy storage provide a viable decentralized alternative, with rural Kenya offering representative deployment conditions. In this study, Imbirikani in Kajiado County, Kenya, was selected as a case site because of its alignment with typical off-grid microgrid contexts. This study compares lithium-ion (Li-ion) and vanadium redox flow battery (VRFB) energy storage technologies within HRES deployed in rural Kenya, using HOMER Pro for techno-economic simulations, and cradle-to-grave Life Cycle Assessment (LCA) following ISO 14040/14044, and Analytic Hierarchy Process (AHP), based multi-criteria decision analysis (MCDA) was used. The results indicate that Li-ion systems achieved a lower Levelized Cost of Storage (LCOS) of KSh. 23.17/kWh compared to KSh. 28.32/kWh for VRFBs, primarily driven by higher round-trip efficiency and lower upfront capital costs. However, Li-ion systems exhibit higher Global Warming Potential (GWP) impacts of 0.18 kgCO₂/kWh, relative to VRFBs’ 0.10 kgCO₂/kWh, largely attributable to lithium–cobalt extraction and limited end-of-life recyclability. In contrast, VRFBs demonstrated longer cycle life, full depth-of-discharge capability, and electrolyte recyclability exceeding 80%, thereby supporting improved long term environmental performance. The study contributes an integrated techno-economic, environmental, and decision-analysis framework for evaluating energy storage technologies in rural African micro grids. Therefore, it is evident that, the multi-criteria evaluation highlights Li-ion batteriesas the preferred option for near-term, cost-driven rural micro grid deployment in Kenya, while VRFB technologies are recommended for long-term sustainable energy planning where lifecycle, durability and environmental performance are prioritized.

A Critical Review of Lateritic Concrete: Influence on Strength, Durability, and Sustainability in Construction

J. M. Aremu — 2026-06-02

This paper presents a critical review of lateritic concrete as a sustainable alternative to conventional concrete, with emphasis on its material characteristics, mechanical performance, durability behaviour, and environmental implications. The review synthesizes findings from published studies on laterite-based concrete, including research on partial aggregate replacement, supplementary cementitious materials, fibre reinforcement, and alternative binders. The literature indicates that, under specific mix proportions and curing conditions, partial replacement of conventional aggregates with laterite—commonly within the range of 20–50%—can produce concrete with strength properties comparable to those required for certain structural and non-structural applications. However, performance is strongly influenced by laterite mineralogy, grading, moisture sensitivity, and pore structure. Several studies further reported that the incorporation of materials such as fly ash, palm oil fuel ash (POFA), fibres, and geopolymer binders can improve selected durability and strength characteristics. From an environmental perspective, the reviewed studies suggest reported reductions in embodied carbon and lifecycle impacts, although the magnitude of such benefits varied widely depending on mix design, transport distance, and binder composition. The review also identified key limitations, including regional variability of laterite deposits, inconsistent testing and characterization methods, limited long-term durability data, and challenges related to standardization and large-scale implementation. Future research should prioritize harmonized evaluation protocols, region-specific mix optimization, and field-based performance validation to support the broader application of lateritic concrete in sustainable construction.

Design and Fabrication of a Combined Charcoal Grinding and Moulding Machine

I. Sulaiman — 2026-06-02

The design and fabrication of an affordable biomass processing equipment remain essential for improving small-scale charcoal briquette production in developing regions. This study presents the development and performance evaluation of a combined charcoal grinding, mixing, and moulding machine that integrates size reduction, binder mixing, and compaction into a single system to improve process efficiency and reduce losses. The machine was constructed primarily from mild steel and powered by a 2.2 kW electric motor. Design analyses were carried out to determine the power requirement, shaft dimensions, and mixing chamber capacity. Performance testing was carried out using 10 kg batches of dried charcoal and grinding times used ranged from 11.8 to 12.4 min. The results showed that the total power required by the machine was 1.185 kW, the calculated shaft diameter was 15 mm, while the mixing chamber capacity was 12.1 kg of charcoal mixture. Throughputs between 46.9 and 48.8 kg/h was obtained along with an average of 48.0 kg/h, corresponding to a capacity efficiency of 96.1% relative to the 50 kg/h design target. The moulding unit produced briquettes with uniform dimensions, having an average diameter of 40 mm, height of 35 mm, and mass of 85 g, indicating consistent compaction. Durability evaluation produced an average shatter index of 6.93%, indicating good resistance to breakage during handling and transportation, while combustion testing gave an average ignition rate of 8.04 mm/min, indicating stable flame propagation suitable for domestic cooking applications. The close agreement between experimental and design values demonstrates that the integrated machine operates efficiently and reliably. The developed system offers a simple and effective solution for small-scale conversion of charcoal fines and agricultural residues into densified solid fuel.

Development of an IOT-Based Fuel Level and Geolocation Monitoring System

O. K. Ogidan — 2026-06-02

Fuel theft and frequent vehicle abductions across many African regions inflict heavy economic losses on transportation providers, demanding reliable yet affordable monitoring solutions. Traditional ultrasonic sensors for fuel level detection fall short due to inaccuracies from fuel foaming and the need for invasive tank drilling during installation. This study addresses these challenges by introducing a low-cost, non-invasive telematics retrofit that leverages existing vehicle fuel sensors for real-time fuel level display and geo-location tracking, which are critical tools for fleet management in developing economies with meager resources. The proposed system intercepts the signal cable from the fuel tank sensor to the vehicle dashboard, integrating it with a microcontroller-based data acquisition system. This setup displays fuel levels and GPS coordinates on an LCD screen and streams data to Google Maps via a web application, requiring no tank modifications. The results showed GPS data from the device correlated strongly with mobile phone benchmarks, yielding coefficients of 0.911 for latitude and 0.941 for longitude, validating its precision. These findings demonstrate a practical, retrofit-friendly alternative to ultrasonic methods, enabling theft prevention and efficient fleet oversight without high costs or disruptions. Future work could integrate machine learning to predict fuel consumption, vehicle paths, and driver behaviour.

Development and Properties Characterizations of Shea Nutshell Ash (SNSA) Reinforced Aluminium Metal Matrix Composite

A. Gana — 2026-06-02

Growing interest in sustainable and low-cost engineering materials has encouraged the use of agricultural waste as reinforcement in aluminium metal matrix composites. In this study, shea nut shell ash (SNSA), an abundant agro-waste material was used as reinforcement in AA6061 aluminium alloy to develop an environmentally sustainable composite. The composites were produced using the stir casting technique with SNSA additions of 0, 5, 10, 15, 20, 25 and 30 wt%. Microstructural and phase characterisation were carried out using scanning electron microscopy with energy dispersive spectroscopy and X ray diffraction, while mechanical properties were evaluated through tensile, hardness and impact tests in accordance with ASTM standards. The results showed that SNSA is predominantly carbon based with 88.15 wt% carbon and 7.75 wt% oxygen, while minor elements such as Fe 2.18 wt%, Si 0.36 wt% and Ca 0.31 wt% were also detected. X ray diffraction revealed the presence of hard phases including Fe₃C and MnO together with graphite. In addition, the Mechanical properties revealed that the unreinforced AA6061 alloy exhibited the highest tensile strength of 119.77 MPa and elongation of 12.91%. With increasing reinforcement content, tensile strength decreased to 83.04 MPa at 5 wt% and further to 32.32 MPa at 25 wt%, before slightly recovering to 66.56 MPa at 30 wt%. Conversely, hardness increased from 7.6 HRB for the base alloy to a maximum of 13.5 HRB at 30 wt% SNSA. However, the impact energy improved from 2.64 J for the matrix alloy to 8.33 J at 10 wt% reinforcement and remained above the base alloy for all reinforced samples. Furthermore, the results indicate that moderate SNSA additions of 5 to 15 wt% provided the most balanced combination of hardness, strength and impact resistance. Therefore, the study demonstrates that SNSA is a promising sustainable reinforcement for aluminium matrix composites suitable for cost sensitive engineering applications.

Advanced Control Strategies for Power-to-X Systems: Enhancing Green Hydrogen Production from Variable Renewable Energy Sources

S. O. Oyakhilome — 2026-06-02

The integration of variable renewable energy sources with Power-to-X systems presents critical operational challenges. Conventional control approaches cannot simultaneously optimize hydrogen production efficiency, minimize electrolyzer degradation, respond to dynamic electricity pricing, and provide grid frequency regulation services. Existing proportional-integral (PI) control methodologies prove inadequate for managing these competing demands in systems coupling intermittent solar and wind inputs with electrolysis designed for steady-state operation. Therefore, this research develops and validates advanced control strategies incorporating hierarchical Model Predictive Control (MPC) with adaptive elements for optimizing green hydrogen production from variable renewables. We implement a three-layer architecture separating strategic planning, tactical optimization, and operational execution, validated through comprehensive simulations using realistic renewable profiles from operating installations and experimental testing on a 50kW proton exchange membrane electrolyzer. The results show that the proposed adaptive MPC framework achieves 18.3% higher hydrogen production efficiency during high-variability periods (95% CI: 14.7-21.9%) compared to baseline PI control, with 34.7% reduction in thermal cycling stress, translating to an estimated 22% equipment lifetime extension. Economic analysis demonstrates 12.5% reduction in levelized hydrogen cost through improved capacity utilization and optimized response to electricity price signals. Experimental validation confirms simulation predictions within 8-12% error margins across multiple operating scenarios, with detailed mismatch analysis identifying transient conditions as primary deviation sources. These findings establish practical viability for industrial-scale Power-to-X deployment, demonstrating that advanced control enables dual-purpose operation—simultaneous hydrogen production and grid service provision—essential for renewable energy integration. The modular control architecture facilitates adaptation across diverse electrolyzer technologies and renewable configurations.

Experimental Investigation and Predictive Modelling of Sustainable Concrete Incorporating Rice Husk Ash and Periwinkle Shell Ash

T. A. Ibu — 2026-06-03

Concrete remains the most widely used construction material globally but the durability and performance of concrete structures have become a critical concern in modern construction. Concrete is exposed to chemical attacks that significantly affect its long-term strength and integrity. This study investigated the properties of concrete incorporating blended Rice Husk Ash (RHA) and Periwinkle Shell Ash (PSA) as supplementary cementitious materials, and also developed predictive strength models. Concrete mixes with varying RHA-PSA replacement ratios were produced at a constant water–cement ratio of 0.55 and cured for 3, 7, 28, and 90 days. The ashes were characterized using Energy-Dispersive X-Ray Fluorescence (EDXRF). While aggregates conforming to BS EN standards were used, workability test were performed on the fresh concrete samples and compressive strength, tensile strength, and density were done on the hardened samples. Finally, the properties were modelled and validated using regression analysis. The results indicated that both RHA and PSA contained key oxides (CaO, SiO₂, Al₂O₃, Fe₂O₃). Also, RHA satisfied the ASTM C618 requirement of the sum of SiO₂, Al₂O₃ and Fe₂O₃ of more than 70% with a value of 71.86% indicating their pozzolanic potential. PSA, with a combined total of 3.17% did not meet this pozzolanic threshold but complemented RHA with its high CaO (≈ 88%). RHA and PSA had specific gravities of 1.79 and 2.49 respectively, indicating their potential as lightweight pozzolans, reducing concrete density while maintaining strength. At 28 days, 70% of mixes exceeded the 25 N/mm² target strength, with B7(6%RHA + 4% PSA) achieving the highest compressive strength and B6(5.25%RHA + 4.75% PSA) the highest tensile strength at 28 - 90 days. Predictive models of (R2 = 0.8410) for compressive strength, and (R2 = 0.5899) for splitting tensile strength at 28days curing respectively accurately described strength development for specific mix designs. B7 mix design was recommended where high compressive strength was a priority. While B6 mix ratio is preferable for maximizing splitting tensile strength for cubes/cylinders cured in water. Balanced blend of ≈5–6% RHA and 4–5% PSA enhanced strength, durability, and microstructure, promoting sustainable, high-performance concrete.

Design and Development of Reconfigurable PMSM for Stator Winding Turn Variation Investigation

B. O. Akinloye — 2026-06-03

Permanent Magnet Synchronous Motors (PMSMs) play a central role in modern industries due to their high efficiency and torque density; however, experimental platforms that allow controlled variation of key electromagnetic parameters—particularly stator winding turns—are limited. This paper presents the design, development, and experimental validation of an electromagnetic module based on a laboratory-scale permanent magnet synchronous motor developed to investigate the influence of stator winding variation on torque characteristics. The research integrates analytical design, finite-element simulation, and controlled laboratory experimentation. A permanent magnet synchronous motor prototype was designed from first principles, covering magnetic loading, induced EMF, conductor sizing and winding distribution. A multitap stator winding arrangement was implemented, enabling the effective number of turns to be varied between 40 and 60 without physical rewinding. Finite-element model was developed using ANSYS to predict electromagnetic torque behavior, while experimental tests were conducted using an inverter-fed drive system. Simulation results revealed a non-monotonic torque response, with torque peaking at intermediate winding configurations, 23.29 Nm at 45 turns, before decreasing at higher turn counts, indicating the influence of electrical and magnetic constraints captured within the numerical model. In contrast, experimental measurements showed a stronger torque dependence on winding configuration, with torque increasing from 22.81 Nm at 40 turns to a maximum of 28.94 Nm at 55 turns, followed by a slight reduction to 27.27 Nm at 60 turns. The results confirm that stator winding variation is a dominant but multi-dimensional design parameter in permanent magnet synchronous motor torque performance and that optimal torque occurs within a finite winding range rather than through indefinite turn increase. The developed electromagnetic module serves as a flexible experimental platform for parametric studies in electric machine design, optimization and education.

A Recursive Least Squares-Based Adaptive Fuzzy Logic Approach for High-Performance Maximum Power Point Tracking in Photovoltaic Systems

B. O. Akinloye — 2026-06-03

The growing demand for high-efficiency renewable energy systems has intensified research into advanced photovoltaic (PV) energy optimization techniques. Maximum Power Point Tracking (MPPT) is essential for maximizing energy extraction from PV systems under varying environmental conditions. Among the available techniques, intelligent control strategies such as Fuzzy Logic Control (FLC) and Adaptive Fuzzy Logic Control (AFLC) have attracted considerable attention due to their robustness and adaptability. However, conventional methods, including standard FLC, often suffer from reduced tracking accuracy, slower dynamic response, and increased steady-state oscillations under rapidly changing irradiance and temperature conditions—challenges that are particularly pronounced in tropical environments with frequent atmospheric fluctuations. This study presents the design and simulation of an Adaptive Fuzzy Logic Controller (AFLC) based MPPT system for a PV array integrated with a DC–DC boost converter. The system is modeled in MATLAB/Simulink, where both FLC and AFLC techniques are implemented and evaluated under varying environmental conditions. The proposed AFLC enhances performance by dynamically adjusting its membership functions, scaling factors, and rule weights in real time using Recursive Least Squares (RLS) adaptation. It was observed that Simulation results of the AFLC significantly outperforms the conventional FLC approach. The AFLC achieves a tracking efficiency of 91.36%, representing a 5.78% improvement over FLC. The response time is reduced by 90.9% (from 0.11 s to 0.01 s), while oscillations around the Maximum Power Point (MPP) are decreased by 68.9% (from 18.5% to 5.76%). Furthermore, under partial shading conditions, the AFLC effectively avoids local maxima and extracts up to 15% more power. Overall, the proposed AFLC-based MPPT system offers superior tracking speed, accuracy, and stability, making it a highly effective solution for enhancing PV system performance in dynamic and real-world operating conditions.

Mechanical and Durability Performance of Rice Husk Ash–Periwinkle Shell Ash Blended Concrete under Crude Oil Exposure

T. A. Ibu — 2026-06-03

This study evaluates the mechanical and durability of grade 25 concrete modified with Rice Husk Ash (RHA) and Periwinkle Shell Ash (PSA) under crude oil exposure. RHA and PSA were incorporated at 0–10% replacement of cement by weight, while maintaining a constant water-to-cement ratio of 0.55. Concrete specimens were subjected to two curing regimes: 28 days of pre-curing in water and then followed by 62 days post-curing in crude oil immersion (totaling 90 days), and continuous crude oil immersion for 90 days. Mechanical and Durability were assessed through compressive strength and moisture absorption tests at 90 days of curing in line with BS standards. Microstructural investigations using Scanning Electron Microscopy (SEM) were carried out to examine pore refinement, crack morphology, and hydration products. The results indicate that optimal blends of ≈5–6% RHA and 4–5% PSA produced the best performance. They achieved higher density (eg.C7=2730kg/mm3 and W7=2803 kg/mm3), lower moisture absorption (e.g. W7=0.1785% and C6-0.486%), and improved retention of mechanical strength (e.g. W7=20.5N/mm2 and C9=16.0N/mm2) compared to control samples. Water-cured specimens consistently outperformed those in crude oil by 7.87% in strength, yet RHA–PSA concretes exhibited slower strength loss and reduced microcracking under crude oil exposure. SEM images confirmed denser C–S–H gel networks and refined pore structures at optimal dosages, whereas higher ash contents increased porosity and susceptibility to deterioration. The findings demonstrate that moderate incorporation of RHA and PSA enhances both the mechanical and durability of concrete in crude oil environments (C7=15.0N/mm2), making these materials promising sustainable additives for infrastructure exposed to petroleum-polluted conditions.

A Review on Production and Performance Evaluation of Briquettes from Rice Husk, Sawdust, And Black-Currant Leaves for Sustainable Energy Production

E. F. Akinola — 2026-06-03

The global search for sustainable and decentralized energy solutions has resulted in increased interest in biomass briquetting technologies. This study presents a review of briquettes produced from rice husk, sawdust, and black-currant leaves, focusing on physicochemical properties, combustion performance, thermogravimetric behaviour, and techno-economic feasibility. The review was conducted using Scopus and Google Scholar databases for studies published between 2020 and 2025. An initial pool of 213 articles was screened using defined inclusion criteria, resulting in 46 relevant studies for detailed analysis. The results indicate that sawdust exhibits superior fuel properties with calorific values of 16–19 MJ/kg and low ash content (0.5–3%), leading to higher thermal efficiency (30–35%), while rice husk shows high ash content (15–25%) due to silica, which limits combustion efficiency. Black-currant leaves demonstrate high volatile matter (62–68%), enhancing ignition but requiring binder support due to low lignin content. Thermogravimetric analysis reveals three-stage degradation behaviour with activation energies ranging from 160–250 kJ/mol. Composite briquettes improve combustion stability by balancing ignition and durability characteristics. Techno-economic analysis shows production costs of 30–55 USD/tonne with potential profit margins of 40–50% under favourable conditions. Despite increasing research on biomass briquetting, studies are largely concentrated on conventional feedstocks such as rice husk and sawdust, while leaf biomass like black-currant leaves remains insufficiently characterized, particularly in terms of densification and combustion behaviour. In addition, most studies assess physicochemical, combustion, or thermogravimetric properties in isolation, with limited integration into a unified framework linked to real stove performance.

Production and Evaluation of African Star Apple (Chrysophyllum Albidum) Seed Oil as a Non-Edible Feedstock for Biodiesel Production

T. E. Kolajo — 2026-06-03

The ever-increasing demand for sustainable and renewable energy has intensified research into non-edible oil feedstocks for the production of biofuels. This study investigates the production of biodiesel using African Star Apple (Chrysophyllum albidum) seed oil as feedstock. The seeds were processed to remove the seedcoat while oil was extracted from the cotyledon by superheated solvent extraction at varying seed particle sizes of <0.5, 2.0 and 4.0mm respectively. The extracted oil was subjected to physical (density, colour, odour) and chemical characterisation (free fatty acid and acid value, iodine tests). Biodiesel was produced using the two-step reaction process (acid esterification and transesterification) and was tested for its physiochemical properties (density, kinematic viscosity and cetane number) and microstructural properties following the established ASTM and EN standards. The results show that the oil yield varied significantly across particle sizes, with the highest yield obtained from <0.5mm particle size, with an overall average yield of 8.37%. It was observed that the extracted oil contained 3.948% free fatty acid (FFA) content with saponification value of 201.8 mg KOH/g. Furthermore, the biodiesel properties (Density at 0.88g/cm, Kinematic Viscosity at 4.2mm/s, and Cetane Number at 52) were found to be in compliance with the established fuel standards, thus validating the use of C. albidum seed oil as a potential viable biodiesel feedstock. Overall, the physicochemical profile of C. albidum seed oil proves its effectiveness as a viable, alternative biodiesel feedstock.

Design Modification and Fabrication of a Dual-Purpose Rice Processing Machine

A. Afolabi — 2026-06-03

This study presented the design, fabrication, and performance evaluation of a dual-purpose rice processing machine that integrated threshing and milling operations into a single unit to address the inefficiencies of conventional post-harvest rice processing. The machine was designed using standard mechanical design principles and fabricated with locally available materials to ensure affordability, durability, and ease of maintenance for small- and medium-scale rice processors. A 1.5 hp electric motor served as the prime mover, driving both the threshing drum and milling rollers through a belt and pulley transmission system. Performance evaluation was conducted through a series of preliminary and formal tests using paddy rice samples. Experimental results showed a threshing efficiency of 66%, milling efficiency of 69.69%, and rice husk recovery of 39.6%. When operated as an integrated single-pass system, the machine achieved an overall operational efficiency of 46%, producing 2.3 kg of milled white rice from 5.0 kg of paddy. Although this overall efficiency is moderate and lower than that of many optimized conventional rice processing systems, it remained acceptable for a low-cost prototype and demonstrated the feasibility of integrating threshing and milling in a compact unit. These results highlighted the potential of the machine to reduce processing time, labor, and equipment cost. However, further optimization particularly in grain transfer mechanisms, threshing consistency, and milling clearance adjustment is required to improve performance. It is therefore recommended that future designs should focus on improving component alignment, enhancing separation efficiency, and conducting extended field testing under varying moisture and load conditions to achieve higher overall efficiency and reliability. Overall, the developed machine offered a practical and cost-effective solution for improving local rice processing and enhancing food security in rural communities.

Solar Irradiance Estimation Using Deep Artificial Neural Network: A Case Study of Yola, Nigeria

M. Aminu — 2026-06-03

Accurate estimation of solar irradiance is essential for the design, optimization, and operation of solar energy systems, particularly in regions with high renewable energy potential such as Yola, Nigeria. Traditional empirical and regression-based models often struggle with nonlinear relationships between meteorological parameters and solar irradiance, leading to reduced accuracy. To address this limitation, this study developed a Deep Artificial Neural Network (DNN) model to estimate daily global solar irradiance using ten years (2015–2025) of meteorological data, including sunshine duration, temperature, humidity, wind speed, and cloud cover. The data were preprocessed, normalized and used to train a multi-layered DNN in MATLAB R2024b. Model performance was evaluated using Root Mean Square Error (RMSE), Mean Bias Error (MBE), and Mean Percentage Error (MPE). Simulation results revealed that the DNN achieved high predictive accuracy, with RMSE of 15 W/m², MBE of 2 W/m², and MPE of 5.0%. For comparison, conventional Angstrom–Prescott empirical model applied to the same dataset gave RMSE values ranging from 28 W/m², confirming the superiority of the DNN. The DNN model also demonstrated strong correlation with measured solar irradiance (R² = 0.984), highlighting its robustness in capturing nonlinear meteorological interactions. The proposed DNN-based approach provides a more reliable tool for solar irradiance estimation in Yola and could have potential applicability to other regions in sub-Saharan Africa.

Recent Advances in Solar Steam Generators: Photothermal Materials, Structural Architectures, and Energy Conversion Applications

F. M. Kajiama — 2026-06-03

Solar steam generation has emerged as a highly efficient and sustainable technology for water purification, desalination, and decentralized energy applications, particularly in off-grid and resource-constrained regions. Unlike conventional solar thermal systems that rely on bulk water heating, solar steam generators utilize localized interfacial heating to achieve high solar-to-vapour conversion efficiencies under low solar concentration. This review presented an analysis of recent advances in solar steam generation technologies, focusing on photothermal materials, structural design strategies, performance characteristics, and system integration pathways. Carbon-based materials, plasmonic nanoparticles, semiconductor oxides, and biomass-derived absorbers were examined in terms of optical absorption, thermal management, cost, and scalability. The methodology employed was systematic analytical literature review, drawing on peer-reviewed articles, conference proceedings, and review papers indexed in Scopus, Web of Science and Google Scholar, published between 2010 and 2025. Key findings revealed that carbon-based and biomass-derived photothermal materials can achieve solar-to-vapour conversion efficiencies of 80–93% under one-sun illumination, while interfacial floating and three-dimensional structural designs offer superior salt rejection and heat localization compared to conventional bulk-heating configurations. Integration of solar steam generators with thermoelectric generators and organic Rankine cycle systems was shown to be feasible for off-grid electrification, though long-term durability and techno-economic viability under field conditions remain critical outstanding challenges.

Development of a Machine Learning-Driven Automated Waste Sorting System

A. A. Aribisala — 2026-06-04

The rapid growth of municipal solid waste presents environmental and health challenges, while manual sorting remains inefficient and hazardous. This study develops a prototype machine learning–driven automated waste sorting system designed for low‑cost deployment. The system integrates an ESP32‑CAM module for image capture, a MobileNetV2 convolutional neural network (CNN) transfer learning technique for classification, and a servo‑actuated mechanical sorting mechanism. Waste items are classified into biodegradable and non‑biodegradable categories, with system control managed through an ESP32 microcontroller and real‑time communication via WebSocket. The model was trained on 90 live images with an additional 2356 images augmented from an online database. The system achieved an accuracy of 93.57% on the test set. While this result confirms the system's feasibility, its generalizability is currently restricted by lighting sensitivity, a limited dataset, and an inability to classify wet waste. The prototype highlights the potential of combining embedded AI and mechatronics for sustainable waste management, supporting circular economy goals. Future work should expand datasets aimed at mitigating overfitting and addressing high intra-class variance, incorporate synthetic data generation to enhance model robustness, and explore edge inference for reduced latency.

An Assessment of the Influence of Grain Refiners and Modifiers on The Performance Characteristics of Aluminum Alloy (AA-2618) Castings

B. Abdulkareem — 2026-06-04

This study evaluates the influence of grain refiners and modifiers on the microstructure and mechanical performance of AA-2618 aluminum alloy castings. A titanium-based master alloy (Ti–Al) was employed as a grain refiner, while strontium chloride (SrCl₂) was used as a chemical modifier. Each additive was introduced at 0.12 wt%, both individually and in combination, to investigate their effects on grain structure, eutectic phase morphology, and the resulting mechanical properties. Cast samples were produced under controlled conditions and characterized using optical microscopy and standard mechanical tests, including Brinell hardness, tensile strength, impact energy, and percentage elongation. The results from Microstructural analysis revealed that SrCl₂ modification significantly altered the eutectic morphology and refined the solidification structure, resulting in an average grain size reduction of approximately 28–32% compared with the untreated alloy. This refinement translated into improved mechanical performance, with tensile strength increasing from 141.76 MPa to 169.92 MPa (≈19.9% improvement), elongation increasing from 3.99% to 5.56% (≈39.3% improvement), and impact energy rising from 2.55 J to 2.58 J (≈2% improvement). In contrast, the addition of Ti–Al grain refiner alone resulted in reduced tensile strength (112.90 MPa) and impact energy (2.33 J), attributed to the formation of coarse TiAl₃ intermetallic particles that acted as crack initiation sites. However, the combined Ti–Al + SrCl₂ treatment did not exhibit synergistic behavior and produced the lowest hardness (53.57 HB) and tensile strength (93.58 MPa), indicating competitive interactions that hindered effective grain refinement and modification. Overall, the results demonstrate that strontium-based modification offers the most effective approach for enhancing the microstructural integrity and mechanical performance of AA-2618 aluminum alloy castings.

Effect of Semi- Solid Squeeze Casting Parameters on Mechanical Properties of Recycled Aluminium Alloy Scrap

F. E. Omagu — 2026-06-04

The growing demand for sustainable materials has heightened interest in recycling aluminium alloys for engineering applications. This study investigated the recycling of aluminium alloy from automobile cylinder head scrap using semi-solid squeeze casting, optimized via a Taguchi L9(3³) design. Adopted process parameters were squeeze pressure (100–140 MPa), slurry temperature (590–630 °C), and die preheating temperature (220–240 °C). Their effects on tensile strength and hardness were analyzed using signal-to-noise ratios and ANOVA. Also, the recycled alloy was identified as an Al–Si type, containing 6.75% Si and 0.36% Mg, along with trace amounts of Fe, Cu, Mn, and Zn. In addition, tensile strength ranged from 228 to 233 MPa, while hardness ranged from 72 to 78 BHN. The maximum tensile strength of 233 MPa was achieved at 100 MPa squeeze pressure, 590 °C slurry temperature, and 220 °C die preheating temperature. The maximum hardness of 78 BHN occurred at 140 MPa squeeze pressure, 630 °C slurry temperature, and 220 °C die preheating temperature. Similarly, the ANOVA revealed that die preheating temperature had the greatest influence on tensile strength (64.76% contribution), while squeeze pressure and slurry temperature most strongly affected hardness (49.57% each). Furthermore, confirmation tests at optimal parameters yielded 231 MPa tensile strength and 77 BHN hardness values comparable to those of commercial A356 alloy (258.5 MPa tensile strength, 75 BHN hardness). These findings demonstrate that Taguchi-optimized semi-solid squeeze casting can produce recycled aluminium components with excellent mechanical properties, promoting sustainable manufacturing.

FPGA-Based Deep Learning Processor: A Review

S. Hussaini — 2026-06-04

The rapid adoption of deep learning across diverse application areas has intensified the demand for specialized hardware capable of efficiently executing computationally intensive neural networks at scale. Field-Programmable Gate Arrays (FPGAs) have emerged as a prominent solution, offering a unique combination of high parallelism, low latency, and energy efficiency. Despite these advantages, research remains fragmented, with challenges in standardizing architectures, optimizing design flows, and supporting emerging neural network models, including transformers and generative architectures. This review systematically examined recent developments in FPGA-based deep learning processors, focusing on architectural design strategies, optimization methodologies, and deployment across both cloud and edge environments. A structured survey approach was employed, analyzing experimental evaluations and comparative studies of FPGA accelerators for convolutional, recurrent, and next-generation neural networks. The analysis demonstrated that FPGA-based designs consistently achieved superior energy efficiency compared to GPUs and provided scalable solutions for edge inference, though limitations persist in programmability and toolchain maturity. The findings highlighted FPGAs’ potential as critical enablers for next-generation intelligent systems while emphasizing the need for higher-level abstractions, automated design-space exploration, and seamless integration with evolving machine learning frameworks.

Investigation of Geotechnical Properties of Collapsible Soils Within Maiduguri Metropolis

L. M. Kalsari — 2026-06-04

This work presents the experimental study to investigate the geotechnical properties of the collapsible soils within Maiduguri Metropolis, Borno state, Nigeria. Ten Soil sampling points (test pits) were considered from five different locations within the town and labelled as A1-A5 (Dikwa, Damboa, Baga, Jos and Bama roads). The samples were obtained with the aid of a hand auger, shovel, 100mm Polyvinyl chloride (PVC) pipes, scrapper and preserved in Polyethene bags and prepared wooden boxes to avoid moisture loss. Particle size distribution revealed that the soils were predominantly sand with traces of gravel and classified as A-3(0) according to the American Association of State Highway and Transportation Officials (AASHTO) and SP in accordance with the Unified Soil Classification System (USCS). The compaction characteristics showed that optimum moisture content (OMC) ranged between 9.0-15.1% and maximum dry densities (MDD) ranging between 1.57-1.92g/cm3 while colours ranged from brown to rich brown. The oedometer test affirmed the existence of collapsible soils in the studied locations while collapse potential (CP) ranged between 1.50-12.20%. The shear strength test revealed low values of cohesion (c) which ranged between 0-1 kPa with an angle of internal friction (ᶲ) ranging between 5-9º. The ultimate bearing capacity result revealed a range between 14.40-86.80 kN/m2 and safe bearing capacity ranging between 20.20-86.80 kN/m2 with a mean safe bearing capacity of 46.26 kN/m2. Hence the soils were classified as cohesionless.

Investigating The Combined Effect of Reconductoring and DG Placement on the Load Hosting Capacity of Radial Distribution Networks

O. N. Omogbai — 2026-06-04

The increasing penetration of distributed generation (DG) and the need to accommodate load growth have made load hosting capacity (LHC) a key issue in radial distribution network planning; and feeder reconductoring remains a viable means of modifying network impedance and efficiency. However, the combined influence of reconductoring and DG placement on LHC is not fully explored, particularly under constraints such as voltage rise, reverse power flow, and thermal limits. This study was conducted using the IEEE 33-bus radial feeder, where a 2.5 MW DG operating at unity power factor was sequentially placed across all eligible buses under five distinct reconductoring instances. LHC was determined by incrementally increasing system load using quasi-static backward–forward sweep power flow analysis until constraint are violated, Statistical validation using the Kruskal–Wallis H test was used to assess the significance of the observed changes. The results showed that LHC was governed by a nontrivial interaction between conductor impedance and DG location. For instance, low, uniform impedance profiles deferred upstream constraint violations by maximizing LHC (up to 8.65 MW) when the DG was placed at the terminal bus. Further, high trunk impedance reduced LHC and shifted optimal DG placement toward intermediate or near-source buses to prevent voltage dip in weaker branches. Additionally, when strategically installed feeder-wide, highly resistive conductors with improved X/R ratios partially restored terminal DG placement optimality with moderate LHC. The statistical results (H = 73.03, p = 5.20 × 10⁻¹⁵) confirmed that these variations are significant and nonrandom, highlighting the importance of coordinated co-optimization of reconductoring and DG placement for maximizing LHC and enabling proactive feeder planning.

Assessment of Pedestrian Bridges Impact on Traffic Flow and Pedestrian Safety in Maiduguri, Borno State, Nigeria

Y. Ibrahim — 2026-06-04

Pedestrian bridges play a vital role in improving urban traffic flow efficiency and enhancing pedestrian safety by separating pedestrian movement from vehicular traffic at busy road corridors. This study assessed the impact of pedestrian bridges on traffic flow efficiency and pedestrian safety across four corridors in Maiduguri: GSM Market, Ramat Polytechnic Junction, Gamboru Market and the University of Maiduguri Gate. The study is important because increasing urbanization, high pedestrian activity and rising traffic volumes in Maiduguri have created frequent pedestrian–vehicle conflicts, delays and safety risks that require effective infrastructure solutions. Using an observational approach, data on pedestrian counts, traffic volumes, operating speeds, conflicts and survey responses were collected during peak periods and analyzed using descriptive statistics, ANOVA and Pearson correlation. A total of 1,950 pedestrians were observed across the four locations, with bridge compliance averaging 55%, highest at the University of Maiduguri Gate (62%) and lowest at GSM Market (30%). Average uninterrupted vehicle volumes ranged from 1,050 to 1,250 veh/hr but declined to 910–1,000 veh/hr during pedestrian crossings, representing an average reduction of 16.3%. Similarly, average operating speeds dropped from 38–45 km/h under free-flow conditions to 18–25 km/h during at-grade pedestrian crossings, indicating an average speed reduction of 46.2%. Low compliance, especially in commercial areas, contributed to increased jaywalking and pedestrian–vehicle conflicts. GSM Market recorded the highest conflict rate (11.33 conflicts/hr), while the University of Maiduguri Gate had lower conflicts (8.00 conflicts/hr) and better overall performance. The findings indicated that bridge effectiveness depended on user behavior, surrounding land use, accessibility and enforcement. The study recommended better integration of pedestrian facilities, installation of barriers and fencing, stronger enforcement and sustained public awareness campaigns to improve safety and traffic flow.

Experimental Performance Evaluation of a Solar Air Heater Using Recycled Aluminum Soda Cans Absorbers Under Maiduguri Climatic Conditions

B. G. Jidda — 2026-06-04

This study experimentally investigated the performance of a solar air heater (SAH) constructed using recycled aluminium beverage soda cans as absorber tubes under Maiduguri harmattan climatic season. The research addressed the growing need for low-cost, environmentally sustainable heating systems for applications such as space heating and crop drying in regions with abundant solar radiation. The system was designed as a single-pass solar air collector with dimensions 1.09 m × 0.835 m × 0.15 m and collector area of 0.91 m². The absorber consisted of 96 aluminium soda cans arranged in a 12 × 8 matrix and coated with black paint to improve solar absorptivity. Experiments were conducted in active mode using a 12 V DC fan with air mass flow rate of 0.00113 kg/s and in passive mode airflow movement which occurred naturally through buoyancy-driven convection. The collector was tested at tilt angles of 25°, 30°, 45°, 60°, and 180°. Performance parameters included outlet air temperature, temperature rise, useful heat gain, and collector efficiency. Results indicated that the active system achieved a maximum thermal efficiency of 14 % with useful heat gain of approximately 90W at 45o tilt angle. Also, the passive mode achieved 16% efficiency with optimum performance at 45° tilt angle with maximum useful heat gain of 130.2W. The results confirmed that discarded aluminium cans can be effectively used as low-cost absorber materials for solar air heaters in solar-rich regions, such as Maiduguri.

Investigation of the Extent of Contamination at an Automobile Market in Benin City, Edo State, Nigeria Using Very Low Frequency Electromagnetic Survey

O. J. Airen — 2026-06-04

Automobile spare-part markets pose serious sources of underground pollution in fast-growing cities of the developing world since petroleum products and metal bearing wastes are dumped carelessly. Very Low Frequency (VLF) Electromagnetic (EM) method was used to evaluate shallow contamination of the subsurface at Evbareke automobile spare parts market, Benin City, South South Nigeria. Twenty-two VLF-EM traverses were obtained in this active polluted and also in comparatively uninterrupted control areas to outline the conductive anomalies linked to hydrocarbon and heavy-metal contaminations. A 2-dimensional conductivity model showed extensive and spatially dispersed conductive layers that are mainly found in the depths of 5-20 m. The conductivity anomalies are large-scale when they are located directly below the location of visible surface contamination whereas control traverses experienced weak contrasts in conductivity, which is a confirmation that the anomalies are anthropogenic. The findings indicated that the contamination of the site is superficial in nature, laterally discontinuous and highly dependent on surface spill sites and on local hydrogeological circumstances. This investigation demonstrated that the VLF-EM technique is a very effective, non-invasive technique for contamination plumes mapping in urban automobile markets and also offers baseline geophysical data to aid environmental monitoring and remediation planning in this type of environment.

Suitability of Locally Sourced Soils as Fine Aggregates in Concrete Production - A Review

A. M. Kachalla — 2026-06-04

The increasing demand for concrete has intensified the exploitation of natural river sand used as fine aggregate, resulting in material scarcity, rising construction costs and environmental degradation from excessive sand mining. This has encouraged the search for sustainable alternative materials, including locally sourced soils, for partial replacement of river sand in concrete production. This study presented a structured review of experimental investigations on the use of lateritic, sandy, silty and clayey soils as fine aggregates in concrete. A total of 10 experimentally validated studies published majorly between 2015 and 2024 were systematically reviewed. The review evaluated the effects of these soils on workability, compressive strength, durability and cementitious interactions within the concrete matrix. Findings indicated that well-graded sandy soils and lateritic soils with low clay content can replace approximately 10–30% of river sand without significant reduction in compressive strength. Quantitative analysis showed that optimum replacement levels generally ranged between 15–25%, producing compressive strengths of approximately 24–30 MPa suitable for normal structural concrete applications. The review further revealed that soils containing appreciable silica (SiO₂) and alumina (Al₂O₃) may contribute to secondary pozzolanic reactions and improved matrix densification. However, excessive clay content (>8–10%) increased water demand, reduced workability, weakened cement–aggregate bonding and negatively affected durability performance. The use of locally sourced soils may reduce dependence on river sand and lower transportation costs in developing regions. Although preliminary durability performance at moderate replacement levels was satisfactory, further investigations involving permeability, sulphate resistance, shrinkage, carbonation and long-term durability are required before widespread structural application. The study highlighted the potential of locally sourced soils as sustainable supplementary fine aggregate materials when proper characterization, grading and mix proportioning are adopted.

IoT-Based Carbon Footprint Monitoring and Reduction Platform For Urban Homes

J. G. Ambafi — 2026-06-04

Household energy needs should be governed according to the global warming challenge. However, current IoT solutions for measuring carbon footprint are usually costly, inaccurate or have no user-friendly feedback. The key objective of this study was the development of a new low-cost IoT system that tracks real-time electricity consumption and indoor CO₂ concentration to promote sustainable behaviour. A key design feature of the system is its modularity, with an ESP32 microcontroller at the heart of the system allowing easy integration of calibrated SGP30 gas sensor, energy sensors (ZMPT101B, ZMCT103C), and multi-channel communication. The new software solution used for this study was the CallMeBot API that transmits the data directly to WhatsApp, making it very user-friendly by removing the need to use a mobile app only for this purpose. The tests carried out demonstrated that the average error of the voltage sensor was 1.8%, the Wi-Fi data transmission success was 99.2%, and the SGP30 sensor had a successful dynamic baseline calibration, ensuring accuracy to within ±50 ppm of reference values in steady-state conditions. The experiments revealed the existence of energy consumption differences by a substantial margin: the LED bulb (8.7 W) consumed 92% less energy than the incandescent bulb (107.46 W) and the DC fan (7.5 W) 91% less than the traditional AC fan (82.0 W). The indoor CO₂ levels correlated with the occupancy and ventilation, from a base of approximately 400 ppm to over 1250 ppm in areas with no ventilation. This study demonstrated that a powerful open-source IoT platform can enable households to monitor and reduce their ecological footprint to save energy and improve the indoor environment.

Shear Reliability of Reinforced Concrete Beams: A Form-Monte Carlo Framework

K. U. Unamba — 2026-06-04

Shear failure in reinforced concrete (RC) beams is a brittle and often sudden event that poses serious risks to structural safety. While ACI 318-19 and Eurocode 2 provide deterministic shear design provisions, their embedded partial safety factors do not explicitly propagate the statistical variability of resistance and demand variables, resulting in a design space where reliability levels vary substantially from one beam configuration to another. This study develops a fully integrated probabilistic framework that combines the First-Order Reliability Method (FORM) with large-scale Monte Carlo Simulation (MCS, N = 100,000) to quantify shear failure reliability across a parametric space spanning concrete compressive strengths of 20 MPa to 60 MPa, stirrup reinforcement ratios of 0 to 0.004, and shear span-to-depth ratios of 1.5 to 5.0. All basic variables, covering material, geometric, load, and model uncertainty were assigned probability distributions calibrated from experimental databases and the JCSS Probabilistic Model Code. Additionally, Model uncertainty was characterised from 47 beam tests selected from the ACI-DAfStb database. The results show that, for the Compression Chord Capacity Model (CCCM), the calibrated parameters are bias = 1.01 and COV = 0.13. Similarly, the ACI 318-19 model, which is used as the primary design basis in this study, the validation yields bias = 1.28 and COV = 0.29, reflecting its highest scatter. However, the main results used CCCM-calibrated model uncertainty as the more accurate bound. It was observed that the computed reliability indices ranged from 2.04 to 5.12, with beams lacking transverse reinforcement falling below the code target of 3.5 at all shear span-to-depth ratios. In addition, Live load variability was the dominant uncertainty source (32 to 35% of total variance), followed by concrete strength variability (21 to 24%) and model uncertainty (15 to 16%) respectively. A sensitivity analysis confirmed that the results are robust to plausible distribution alternatives, while an elevated concrete coefficient of variation of 0.20, a representative of Nigerian construction site conditions, reduced the reliability index by approximately 0.30 units. Therefore, a reliability-consistent shear partial safety factor of approximately 1.58 is recommended, compared to the ACI equivalent of 1.33. Interestingly, it is clear that the study showed direct implications for code calibration under Nigerian Standards (NIS 369), and the open-source simulation framework is available to support national code revision efforts.