FACULTY OF ENGINEERING

This research examines how sodium hydroxide (NaOH) influences the flow characteristics of purified gum Arabic-based drilling mud formulations, positioning them as eco-friendly substitutes for conventional synthetic additives. The experiment involved developing seven initial formulations combining bentonite with different polymer systems: xanthan gum, gum Arabic, and mixtures of gum Arabic with either cocoyam starch or ginger extract in proportions of 50/50 and 75/25. Subsequently, selected formulations underwent alkaline modification using NaOH at measurements of 3.0g, 7.5g, and 15.0g to replicate varying pH environments.
Flow behavior parameters encompassing plastic viscosity (PV), yield point (YP), gel strength, and mud weight were determined through Fann viscometer measurements and evaluated against three mathematical model frameworks: Bingham Plastic, Power Law, and Herschel-Bulkley models.
Experimental findings demonstrated that 50g of gum Arabic delivered comparable rheological characteristics to 1g of xanthan gum under neutral conditions. The introduction of alkaline treatment produced substantial modifications in fluid behavior, with response patterns dependent
on both the specific polymer-starch pairing and alkalinity level. The most remarkable transformation occurred in the gum Arabic-cocoyam (50/50) formulation treated with 7.5g NaOH, which demonstrated PV of 65 cp and YP of 180 lb/100ft² corresponding to increases of 261% and 1025% respectively relative to the 3.0g NaOH variant. The gum Arabicginger combination displayed considerable viscosity enhancement (PV = 108 cp with 7.5g NaOH) yet revealed temporal degradation of gel structure at elevated alkalinity levels. Every alkalinetreated system manifested pseudoplastic (shear-thinning) characteristics with flow behavior indices (n) spanning 0.3 to 0.948, validating their appropriateness for drilling fluid applications. Comparative model analysis indicated that the Herschel Bulkley model most accurately characterized the behavior of alkaline modified natural polymer systems, whereas both Bingham Plastic and Power Law models exhibited substantial prediction errors, especially under highalkalinity conditions. These results established that purified gum Arabic, when strategically combined with indigenous starches, (cocoyam & ginger) and subjected to pH optimization, represents a viable, environmentally degradable, and economically advantageous alternative to synthetic drilling fluid components, delivering ecological advantages while preserving operational performance standards required for petroleum drilling activities.

The growing demand for reliable and sustainable energy solutions in Nigeria has driven the need to investigate renewable energy sources for various agricultural uses. This project centers on designing, analyzing, and implementing a 3.5 kVA solar photovoltaic (PV) system to power essential equipment in a small-scale fish farming operation. The study aims to provide an environmentally friendly and cost-effective alternative to conventional power sources such as fossil fuel generators, which are often expensive to maintain and environmentally harmful. The system was designed to power critical loads, including surface and submersible water pumps, lighting systems, and aeration devices, all vital for maintaining healthy aquatic conditions and ensuring efficient fish production. The design process involved detailed load estimation, component selection, and sizing calculations for the solar panels, inverter, charge controller, and batteries. The selected system components included six 350 W solar panels, a 3.5 kVA inverter, two 12 V tubular batteries (250 Ah each), and an MPPT charge controller. Upon installation and testing, results showed that the system provided a stable power output with an average efficiency of 85%, maintaining continuous operation of the fish farm equipment for over 10 hours daily

This study investigates how optimising injection parameters can improve oil recovery performance in black oil reservoirs using enhanced oil recovery (EOR) techniques. Using CMG's IMEX and STARS simulators, this research examined the influence of injection rate and pressure variations on reservoir recovery efficiency. Three EOR techniques were examined: waterflooding, polymer flooding, and steam injection. Multiple simulation scenarios were conducted on a three-dimensional reservoir model to determine the optimal parameter combinations for maximising oil production. Analysis revealed that injection rate and pressure significantly influenced overall recovery efficiency. While waterflooding outperformed primary depletion methods, polymer flooding yielded the best results in terms of recovery factor and total oil produced, primarily by enhancing sweep efficiency and minimising water production. Steam injection improved recovery by reducing oil viscosity via heat transfer, though it ranked second to polymer flooding under the modeled conditions. Based on the simulation results, polymer flooding emerged as the most effective method for the studied reservoir conditions, indicating strong applicability for Niger Delta black oil reservoirs.

This study investigates the potential of eggshell waste as a reinforcement material in aluminum matrices for kitchenware applications, aiming to enhance material properties. Composites were fabricated with 7%, 10%, and 13% eggshell reinforcement and subjected to tensile testing, Brinell hardness testing, Differential Scanning Calorimetry (DSC), Scanning Electron Microscopy (SEM), and Energy-Dispersive Spectroscopy (EDS) to assess mechanical, thermal, and microstructural properties. Tensile testing revealed a significant increase in Ultimate Tensile Strength (UTS) with 13% reinforcement, reaching 134.29 MPa, though ductility was reduced. SEM analysis of the 10wt% composite showed a finer textured structure but non-uniform particle distribution. EDS confirmed calcium presence, and showed reduced oxygen content. Brinell hardness exhibited a positive correlation between the weight percentage of eggshell in the aluminum composite, which showed that higher eggshell content within the tested range leads to increased hardness. DSC indicated that eggshell addition altered thermal characteristics, with the 13wt% composite showing a slightly higher melting temperature and changes in heat of fusion. These results demonstrate that eggshell reinforcement enhances the tensile strength, hardness and modifies the thermal behaviour of aluminum

This project develops an automated MATLAB tool to verify bridge deck design compliance with Nigerian and major international codes (NHBC,AASHTO LRFD, Eurocode 2). It solves a practical problem in contexts where manual checks are slow, error-prone, and commercial software is costly or not tailored to local regulations. Using a descriptive-developmental approach, the work collects relevant code requirements, designs a modular system, implements the compliance engine in MATLAB, and adds a user-friendly input interface plus an automated reporting module. The tool accepts geometry, material and load data, lets the user pick the design code, and runs checks for bending moments, shear forces and deflections at both Ultimate and Serviceability Limit States. In short, the project provides a practical, scalable, and standardized solution that
improves accuracy and efficiency in bridge-deck code compliance, helps bridge the gap created by limited access to commercial software, and supports safer infrastructure design in Nigeria.

This research focuses on modeling and simulating CO₂ injection and storage in a depleted sandstone reservoir using the CMG-GEM compositional simulator to evaluate the potential of geological carbon sequestration as a sustainable emission reduction strategy. A 3D reservoir model was constructed based on available structural and petrophysical data to replicate the dynamic behavior of CO₂ during and after injection. The simulation was performed under varying pressure and compositional conditions to assess injectivity, storage capacity, and reservoir response over a 69-year period. Results revealed effective CO₂ migration through the formation, with plume dispersion influenced by permeability variations across the ten layers. The estimated total CO₂ storage capacity of the reservoir was approximately 136,863 tonnes, indicating substantial potential for long-term containment. Pressure analysis showed a gradual and controlled buildup within safe limits, confirming caprock stability and the absence of leakage or fracture risk. Additionally, the molality plots demonstrated consistent distribution of CO₂ within the formation, with concentration stabilization after a five-year halt and resumption of injection in 2050, reflecting strong reservoir retention. Overall, the study confirms that the selected depleted reservoir can serve as a viable site for CO₂ sequestration. The findings also highlight the importance of optimizing well placement, incorporating residual and mineral trapping mechanisms, and extending simulation timeframes to improve prediction accuracy and long-term storage performance.

This research investigated the utilization of polypropylene (PP) waste as an additive in the production of sandcrete blocks, aimed at promoting sustainable waste management and reducing the environmental impact of plastic pollution. The study sought to determine the influence of varying polypropylene waste contents on the physical and mechanical properties of sandcrete blocks, thereby evaluating its suitability as a construction material modifier. The experimental work involved producing paving stone specimens with 0%, 1%, 2%, 3% and 4% polypropylene waste by weight of sand. Aggregates were first characterized through specific gravity and sieve analysis to ensure conformity with standard specifications. Sandcrete blocks were then cast, cured in water, and tested for water absorption and compressive strength at 3 and 7 days of curing, following procedures outlined in relevant British Standards. This methodology ensured uniformity in mixing, curing and testing, allowing a clear assessment of polypropylene’s effect on the samples’ performance. The results showed the polypropylene addition influenced both durability and strength properties. Water absorption ranged between 0.64% and 2.88% with the lowest value recorded at 4% PP content, suggesting improved impermeability at higher plastic dosages. Compressive strength ranged from 11.41Mpa and 16.07Mpa, with optimum strength achieved at 1% PP addition, after which a gradual reduction is observed. It was concluded that the inclusion of polypropylene waste up to 1% can enhance strength and durability without compromising structural performance. The study recommends using low dosages of polypropylene waste in sandcrete blocks production and encourages further research into improving interfacial bonding through surface modification and longer curing periods to
maximize the material’s potential for sustainable construction.

Efficient water management is important for sustainable agricultural production, particularly in regions experiencing climatic variability and limited water resources. This study focuses on determining evapotranspiration rates for maize (Zea mays) and rice (Oryza sativa) crops using selected evapotranspiration models under the climatic conditions of Ovia North East LGA, Edo State. Two ET models- the Blaney Morin Nigeria (BMN) and Hagreaves- Samani methods were semployed to estimate reference evapotranspiration (ETo) based on meteorological data obtained from the Nigerian Institute for Oil Palm Research (NIFOR) station. Crop evapotranspiration (ETc) was subsequently derived by applying crop coefficients (Kc) corresponding to the different growth stages. The study compared the performance of both models to evaluate their suitability for local conditions. Results indicated that the BMN model, which uses relative humidity alongside temperature and daylength, produced ET estimates more consistent with humid tropical conditions than the temperature based Hagreaves- Samani model. It was also found that using BMN instead of Hagreaves- Samani model reduces estimated irrigation demand by 85% for both maize and rice, corresponding to water savings of about 8,587 m³/ha and 10,230 m³/ha and approximate energy savings of 390kWh/ha for maize and 456kWh/ha for rice. The findings highlight the importance of using locally calibrated ET models for accurate irrigation scheduling and water resource management. This study provides valuable insights for improving water use efficiency, enhancing crop yield, and promoting climate smart agricultural practices in southern Nigeria.

This project addresses critical operational limitations in locally manufactured yam pounders by designing and implementing an adaptive Variable Frequency Drive (VFD)-based speed controller for a 1 HP single-phase yam pounder motor. Traditional yam pounding machines operate at fixed speeds, resulting in inconsistent pounding results, food quality degradation, limited user control, energy inefficiency, and accelerated machine wear. These shortcomings arise from the inability to accommodate variations in yam texture, moisture content, quantity, and regional preferences for different pounded yam consistencies. The primary objective of this work was to design, implement, and evaluate a speed control system that enables variable-speed operation while maintaining torque stability and energy efficiency. The system employs a microcontroller-based VFD architecture utilizing Arduino Due for Sinusoidal Pulse Width Modulation (SPWM) generation, IR2110 gate drivers for power stage control, and a full H-bridge inverter configuration with IGBTs. The control strategy implements Voltage-to-Frequency (V/f) control to maintain constant magnetic flux across varying operational frequencies, ensuring consistent torque output from 0 to 50 Hz. Comprehensive testing was conducted in progressive stages, beginning with low-voltage functional verification, followed by full-voltage no-load testing, and culminating in motor load testing with the 1 HP yam pounder motor. The system successfully demonstrated linear speed control from 0 to 2850 RPM with smooth torque response and minimal vibration. Key performance metrics included stable DC bus voltage at 325 V, accurate PWM carrier frequency of 10 kHz, maximum motor current draw of 4.2 A (within the 4.5 A rating), IGBT temperature of 42°C after 30 minutes of operation, and Total Harmonic Distortion (THD) of approximately 8.5% in the output voltage waveform.

This study focused on the analysis of load distribution in reinforced concrete (RC) bridge decks using the Guyon–Massonnet–Bares (GMB) method, enhanced through artificial intelligence (AI) and MATLAB integration. The primary aim was to simplify and automate the lengthy manual calculations typically associated with the GMB method by employing AI-assisted computation and visualization tools. Bridge deck parameters were obtained for a 25 m span bridge, and traditional analytical procedures were performed to determine the composite moment of inertia, centroidal properties, bending moments, and required reinforcement area. To improve efficiency, ChatGPT was utilized to generate MATLAB scripts based on defined parameters, enabling automated computation, graphical validation, and comparison of results with manual calculations. The generated MATLAB program successfully reproduced the analytical outcomes, verified bending moment distributions, and produced visual outputs such as load distribution profiles, bending moment diagrams, and influence lines. The integration of AI in bridge analysis effectively reduced human error, saved computational time by approximately 75%, and served as a dynamic learning platform for engineers and students. Benchmarked against classical GMB results, the AI-enhanced system achieved over 95% predictive accuracy, confirming its reliability and ability to simplify complex structural analysis without compromising computational precision