ABUAD Journal of Engineering Research and Development (AJERD)

Techno-economic Evaluation of Grid-connected Hybrid Energy System Based on Run-of-River and Solar Energy Plants for Sustainable Electrification of a Rural Community

Abdulkadir Adamu — 2025-05-06

The connection between energy access and greenhouse gas emissions is an issue that continues to garner attention. Presently, hundreds of millions of people globally do not have access to sufficient electricity, and those who do, rely on expensive fossil resources characterized by greenhouse gases. A viable solution is to explore renewable energy (RE) sources to satisfy the electricity demand and curtail the effect of greenhouse gases. This study performed a techno-economic analysis of a grid-connected hybrid RE system that included micro-hydro and solar photovoltaic power plants for a Nigerian rural community. The optimal system, according to the analysis done with HOMER software tool, has an overall NPC, operating cost, and LCOE of $3,202,139.00, $37,515.81, and $0.06053/kWh, respectively. A 98.1 kW micro-hydro turbine, a 150 kW converter, 100 kW solar panels, and 704 battery strings constitute the system components. An annual emission of 4,483 kg of CO₂, 0.356 kg of CO, 22.5 kg of SO₂, 4.86 kg of NO, and 1.66 kg of particulate matter will be released into the atmosphere. The implementation of this hybrid power system will not only increase access to energy but also help lessen greenhouse gas emissions.

Principal Component Analysis-Multilinear Perceptron-based model for Distributed Denial of Service Attack Mitigation

Opeyemi Oreoluwa Asaolu — 2025-05-06

The increasing occurrence of Distributed Denial of Service (DDoS) attacks has caused significant disruptions in global network services, overwhelming targets by flooding them with requests from various sources. This ease of execution and gaining entry to distributed systems for rent has led to increasing financial losses. This paper addresses the growing challenge of IoT devices-targeted Distributed Denial of Service (DDoS) attacks within 4G networks. In this study, a PCA-MLP (Principal Component Analysis-Multi-Layer Perceptron) intrusion detection model combined with a packet-filtering firewall for enhanced prevention is presented. The firewall, utilizing IPtables, selectively permits traffic from trusted sources, successfully blocking nearly 70% of DDoS threats. The PCA-MLP model proposed in this study demonstrated high performance, accurately identifying different types of DDoS attacks with an overall accuracy of 95.35%.

Development and Evaluation of Mechanical Properties of Rubber Matrix Composite for Automobile Transmission Belt Application

Eugenia Obiageli Obidiegwu — 2025-05-10

The importance of automobile transmission belts (ATB) in mechanical systems cannot be overemphasized. In developing countries, conventional ATB are mostly imported. Most of the imported ones lack sufficient strength, which makes them prone to frequent fracture, they are weak and break easily. This could lead to accidents and damage to engines. Also, frequent replacement of these belts increases the cost of maintenance. In this study, Rubber Matrix Composite has been developed using natural rubber reinforced with polyester fiber and carbon black particulates to modify and overcome these challenges. The produced samples were subjected to physical and mechanical tests. It was observed that the composite hardness increased gradually as polyester fiber reinforcement increased. The sample with fiber reinforcement of 8% exhibited a hardness value of 25.6 HV. Also, the sample without carbon black showed higher levels of water absorption of 20.5%, other samples showed lower levels of water absorption. The result of tensile strength revealed that the sample reinforced with only carbon black exhibited a low tensile strength of 30.30MPa, while the sample reinforced with both materials exhibited the highest tensile strength of 52.61MPa. Generally, the composites exhibited an increase in the mechanical properties as the weight percentage (wt.%) of the reinforcement increased. This study established that high-quality ATB can be produced locally using natural rubber and reinforcements.

Dynamic Hospital Resource Scheduling During Pandemics with Stochastic Optimization

Yewande Ojo — 2025-05-13

The COVID-19 pandemic has highlighted the need to effectively manage hospital resources: ICU beds and ventilators. These resources are significant for sustaining life, especially in severe cases. Traditional deterministic models often fall short in addressing the uncertainties associated with patient inflows and resource availability. This paper develops a novel two-stage stochastic programming model which aims to dynamically allocate resources to deal with the variability of inpatient admissions. To this end, the scenarios are developed using Monte Carlo simulation based on the probabilities estimated from the historical data. The model is created in Python language and solved using the Gurobi optimizer in 0.05s, a large-scale scenario optimization analysis problem with 42 variables and 35 constraints. The KPIs show the highest utilization of ventilators at 66. 67% and the average reduction of 53.5 in the number of offers an ICU practical shortfall leading to better patient care and shorter wait times. This research presents a data-driven tool to enhance the decision-making process and the healthcare system's overall readiness to maintain its strategic reserves by implementing flexible staffing models to improve preparation for disasters such as the pandemic. Its stochastic optimization framework makes hospital resource allocation more efficient, offering a scalable, resilient solution for tackling future pandemic challenges.

Experimental Study on the Impact of Soil Type Variations on Compressive Strength and Settlement Characteristics of Spread Footing Foundations

Ubong Nkamare Tobby — 2025-05-13

This research investigates the influence of soil type variations on the compressive strength and settlement behavior of spread footing foundations. Soil properties such as moisture content, dry density, void ratio, cohesion, and internal friction angle play a crucial role in determining how foundations respond to applied loads. Variations in these properties can lead to uneven settlements and structural instability, posing significant challenges in construction. The study aims to provide a comprehensive understanding of these interactions to enhance foundation design and prevent structural failures. We applied machine learning techniques for data analysis and visualized patterns using Power BI, enabling a detailed exploration of the relationships between soil characteristics, compressive strength, and settlement behavior. The results showed that soil cohesion and internal friction angle had the most significant impact on compressive strength, while moisture content and void ratio were key contributors to settlement behavior. The optimized model achieved high accuracy of 82% in classifying settlement levels, reinforcing the dataset's reliability. This research highlights the importance of thorough soil testing and data-driven modeling in foundation design. We recommend integrating predictive models into geotechnical practice to support safer, more resilient structures, especially in areas with diverse soil profiles. The findings provide a valuable tool for engineers to make informed decisions, reducing the risk of foundation failure and enhancing the long-term stability of infrastructure.

Development of Adaptive Resource Allocation and Interference Mitigation for Spectrum Sharing in D2D-Enabled 5G Heterogeneous Networks: A Case Study of Urban Microcell Environments

Ashraf Adam Ahmad — 2025-05-16

Device-to-device (D2D) communication in heterogeneous networks (HetNets) poses significant challenges in resource allocation and interference management, especially within 5G networks where spectrum sharing between cellular users (CUEs) and D2D user equipment (DUEs) is critical. This study developed an adaptive resource allocation framework using Long Short-Term Reinforcement Learning (LSRL), which integrated Long Short-Term Memory (LSTM) networks with Deep Reinforcement Learning (DRL) technique. The proposed approach addressed the dynamic nature of interference in urban microcell environments by leveraging a Hierarchical Data Format (HDF5) dataset generated from network simulations. These simulations incorporate diverse scenarios, including varying user densities, transmission power levels, and interference conditions. The LSRL-based scheme was evaluated against conventional DRL methods, demonstrating notable improvements in network performance. Specifically, the proposed framework achieved up to a 6.67% increase in sum throughput and an 8.2% enhancement in power efficiency, even under dense user conditions. Additionally, the LSRL model proved resilient to variations in D2D pair distances, maintaining robust spectral efficiency and quality of service (QoS). These findings underscore the potential of the LSRL-based adaptive approach for improving resource management in 5G HetNets, particularly in dense urban deployments, and provide valuable insights for optimizing next-generation wireless communication systems.

Development of an Automated Aquarium Monitoring System with an IoT Interface using Google Sheets

Theodore Tochuckwu Chiagunye — 2025-05-18

This paper presents the development of an automated aquarium monitoring system with an IOT interface using google sheets; the system autonomously monitors key water quality parameters temperature, pH, and turbidity while automating fish feeding and water replacement functions. An ESP32 microcontroller serves as the system’s core, control unit which is programmed using C++ to transmit environmental data to a cloud-based Google Sheet. A servo motor dispenses feed precisely every 12 hours, while two DC pumps are triggered automatically when turbidity exceeds 50 NTU, ensuring proactive water quality management. The designed system is powered by a 30W solar panel and a charge controller coupled with a 12V lead-acid battery, allowing continuous operation in off-grid locations. The system performance test was conducted over a period of five days and was validated by comparing the sensor outputs with results of the manual measurements obtained by using laboratory-grade instruments. The results demonstrated high accuracy, with average deviations of only 1.95% for temperature, 2.09% for pH, and 1.96% for turbidity when compared with the result obtained from the manual measurement. Also the automated feeding and water replacement mechanisms operated with 100% reliability by being able dispense the feed from the hoper at every 12 hours interval and changing the water once the turbidity is equals or above 50 NTU. Hence the proposed system successfully enhanced automation, real-time cloud integration, and renewable power supply for improved fish aquarium management, thereby offering a compelling alternative to labour-intensive and manually operated systems while laying the groundwork for intelligent, data-driven fish farming practices.

Design and Implementation of a Renewable Energy System for Wind Turbine Power Analysis at Ikot Akpaden Community

Imo Edwin Nkan — 2025-06-08

Renewable energy plays a crucial role in sustainable development by enhancing human development and economic productivity. Analyzing the pipeline of installed wind farms across Africa reveals that the continent has substantial wind resources, with the potential to expand capacity by over 900% through the addition of 140 planned projects. The design and implementation of a renewable energy system for wind turbine power analysis in Ikot Akpaden Community serve as a valuable demonstration of wind energy’s effectiveness in mitigating high carbon flaring and other environmental pollutants, benefiting both the present and future environment. The analysis evaluates wind velocity and its significant power output based on the design parameters of the system in used. The experiment is carried out between the hours of 8:00 am to 9:00 pm for 7 days. Results show that wind velocity of Akpaden community varies between 2.67 m/s to 4.57 m/s with an average wind velocity of 4.03 m/s, there are limitation of some hours of the day without significant wind velocity but there is no complete 24 hours of a day that could be without free flow of wind energy. Using a wind turbine with a minimum sweep area of 0.283 m², the power output produced by the available wind velocity ranges from 3.0 W to 8.82 W in a second, therefore by comparison with the theoretical power output of 11.32 W using the system designed parameters, there is 78 percent efficiency in the system design. Also, there is significant drop in power output between the hours of 3:00 pm and 4:00 pm as it is shown on the graphical representation which is as a result of decrease in the wind velocity of the area within that time. It is therefore seen that there is a useful power available in the wind velocity of the study region in which when it is collected and stored, can serve as a useful energy for student during their experiment and research purpose. The wind turbine's output power can be improved to a desired percent using turbine with larger blade radius and sweep area.

Detection and Classification of Dress Code Violations in Educational Environments Using Deep Learning

Aminu Suleiman Bashir — 2025-06-08

This paper explores the utilization of deep learning techniques for the detection and classification of dress code violations in educational environments, identifying the challenges of manual enforcement and the potential for systems that are automated. This paper exhibits a model that integrates Faster R-CNN for detection and EfficientNet for classification, which provides an accurate and very efficient system to monitor students’ compliance with the dress code policies. The model was trained on a dataset of images that were collected from Federal University Dutsin-Ma and were classified into “decent” and “indecent” dressing for both male and female students. The result achieved demonstrates that the model works efficiently, reaching a training accuracy of 98% and a validation accuracy of 96%, and with overall scores for precision, recall, and F1-score exceeding 97%, thereby proving its effectiveness in different dress code categories. The Uniformity across the techniques substantiates the feature extraction performance of the model and demonstrates its generalization ability. This paper outlines the benefits of automation in alleviating bias and human error by improving transparency and fairness and enforcing the dress code. The results showed how it is effective by combining powerful deep learning models with strong frameworks to solve problems of classification.

Development of a Portable Electro-mechanical Crack Monitoring Device for Pipeline Steel Materials

Oyewole Adedipe — 2025-06-11

The pipeline infrastructure, particularly in Nigeria face significant challenges arising from defects such as cracks, which could lead to unforeseen leakage of flammable materials, risks to human and aquatic lives and could result in the loss of valuable petroleum products. This paper presents the development of a portable electromechanical device powered by lithium-ion batteries for monitoring surface pipelines for cracks, facilitating timely maintenance to prevent adverse consequences. The device is equipped with two types of electronic sensors mounted on a mobile platform that transmits data to a laptop via microcontrollers (Arduino Nano) and a USB cable. The casing of the device was constructed using polyvinyl chloride modeling board. Three tests were carried out on a 0.75 cm thick test pipe with 21 cm external diameter: No-crack test, initiated crack test, and covered crack test. Operating at 15 cm/s, the device transmitted surface condition data in real-time. The results showed no significant spikes during the no-crack and covered crack tests, while the cracked pipe test revealed spikes of 0.5 cm at positions 20 cm, 29 cm, and 38 cm along the pipe. The tractive analysis of the device indicated a net tractive force of 4.11 N and a slip value of 0.03, confirming effective movement without skidding. This study demonstrated that the developed device is reliable for pipeline monitoring and can significantly contribute to the maintenance of pipeline structures.

Comparison of the Geotechnical Properties of Lateritic Soils of Borrow Pits for Road Construction in Ado Ekiti

Bamidele Alade — 2025-06-13

Lateritic soils are key materials in road construction across tropical regions, but their performance varies based on their geotechnical properties. This study analyzes the geotechnical properties and characteristics of lateritic soils from selected borrow pits in Ado Ekiti, Nigeria, to determine their suitability for subbase and subgrade applications. Four borrow pits, labeled A to D, were randomly selected, and twelve undisturbed soil samples (three from each pit) were collected for laboratory testing. The tests include natural moisture content, specific gravity, grain size distribution, Atterberg limits, permeability, compaction, California Bearing Ratio (CBR), unconfined compressive strength (UCS), and triaxial test. Soil samples from Borrow Pit A, identified as Silty Sand (SM) and classified as A-2-4, showed the highest Maximum Dry Density (1750–1753 kg/m³), low Optimum Moisture Content (12%–14%), fines content of 12%, adequate permeability (2.0 × 10⁻⁵ to 2.2 × 10⁻⁵ cm/s), and unsoaked CBR values of 70%–75%, making them ideal for subbase applications. Borrow Pit B soil samples, categorized as Clayey Sand (SC) and A-2-6, had moderate MDD values (1650–1660 kg/m³), permeability between 1.2 × 10⁻⁵ and 1.4 × 10⁻⁵ cm/s, unsoaked CBR values of 58%–60%, and shear strength of 205–210 kPa, making them suitable for improved subgrades or low-traffic subbases. Borrow Pits C and D, classified as Low Plasticity Clay (CL) under USCS and A-6 and A-7-6 under AASHTO, had MDD values between 1500–1551 kg/m³, fines content of 20%–30%, permeability between 0.4 × 10⁻⁵ and 0.1 × 10⁻⁵ cm/s, unsoaked CBR values below 42%, and shear strength of 180–192 kPa, making them more appropriate for subgrade applications. The study concludes that Borrow Pit A is the most suitable for subbase layers, while Borrow Pits B, C, and D require stabilization, such as lime or cement treatment, to improve their strength and plasticity properties.

Effect of Heat Treatment on the Mechanical Properties of Aluminium 6063 Reinforced with Alumina, Titania, and Hybrid Powders

Anuoluwapo Blessing Bello — 2025-06-30

The research examines the mechanical behaviour changes of alumina and titania-reinforced Aluminium 6063 composites after T6 heat treatment. The stir casting method combined with 3 wt% or 6 wt% reinforcement followed by a heat treatment solution at 520°C for 2 hours, then water quenching and artificial aging at 180°C for 8 hours. Tensile properties and hardness were enhanced through heat treatment such that peak hardness reached 116 HRB in 6 wt% TiO₂ composites. Tensile strength increased by 44.8% in 3 wt% TiO₂ composites (192.8 MPa), and peak hardness reached 116 HRB in 6 wt% TiO₂ samples. The impact strength of materials decreased with reinforcement addition, but heat treatments introduced marginal improvements when working with low reinforcement amounts. The research findings present essential knowledge to improve Aluminium 6063 composites for automotive and aerospace sector applications.

Performance Evaluation of Dough Mixing Machine

Kunle Oni — 2025-06-30

In bread-making, mixing is most crucial process to bring different ingredients together to achieve homogeneity, the quality of dough depends mainly on mixing processes. This study was carried out to evaluate the performance of dough mixing machine designed, by assessing the functional properties of wheat flour for the pasting properties and farinograph characteristics of the flour suitable for use in the mixing machine. A gear-driven electric motor of 1.23 kW maximum power supply with torque of 3.75 Nm was considered for the designed fabrication. The machine operated at 280 rpm with a mixing capacity of 31.9 kg/hr and an average efficiency of 94.7%. The dough mixer performance evaluation results analyzed for pasting property of the flour samples, indicated that flour from the Eagle Flour was the best for bread making with the value of peak viscosity of 792.1 RVU, trough viscosity of 193.6 RVU, breakdown viscosity of 598.5 RVU, setback viscosity of 73.9 RVU, final viscosity of 267.5 RVU, and pasting temperature of 50.2 ^oC. Result analysis shows that, Eagle Flour sample has a water absorption capacity, swelling capacity and bulk density of 152.69 %, 20.78 % and 0.78 g/ml respectively. Then, Farinograph characterized the mixing time, over mixing stability, and dough's rheological characteristics. The physical property of the bread obtained from fabricated dough mixer has a loaf volume of 1850 cm³, specific loaf volume of 4.19 cm³/g, density of 0.15 g/cm³ and oven spring of 0.16 mm. The overall acceptability rating of 94.28% and 89.48% were recorded for the bread from the fabricated and commercial dough mixers, respectively. Hence, 5 kilograms (kg) of components was able to mix properly and effectively in 8.15 minutes on average, which is 36.91 kilograms per hour. The fabricated dough mixer has a good market prospect.

Development of an Automated Counselling System for Nigerian Open and Distance Learning Students' Programme Selection

Jane Ada Ukaigwe — 2025-07-07

Choosing an academic programme or career path is often challenging for prospective students seeking admission to higher education institutions. Many rely on advice from both qualified and unqualified sources, leading to poor programme choices that result in dissatisfaction, poor performance, or dropping out. This study aims to design an Automated Counselling System (ACS) to improve prospective students' programme and career decisions in an Open and Distance Learning (ODL) institution, using the National Open University of Nigeria (NOUN) as a case study. The ACS was developed using Client Architecture and a mixed-method approach. Data was collected through questionnaires distributed via NOUN desk officers at purposefully selected study centers across Nigeria's six geopolitical zones. Of the 240 questionnaires distributed, 180 were returned. Findings indicate that the system was well received, with most users expressing satisfaction in its ability to assist them in making informed, long-term programme choices. The ACS presents an effective solution to the counselling gaps in educational institutions, offering a scalable and reliable alternative to traditional counselling methods. However, further research on how the system can help students manage academic challenges once they are admitted should be investigated. The insights from this study can be applied to other higher education institutions.

Development of an Integrated Human-Computer Interactive Model for Improved User Experience in Gesture-Controlled Smart Mirrors

Ayorinde Joseph Olanipekun — 2025-07-17

The advancement of smart technologies has led to the development of innovative home automation devices, with smart mirrors emerging as a modern convenience tool. This paper focuses on the design and implementation of a gesture-controlled smart mirror, incorporating a two-way mirror, monitor, raspberry pi, gesture-enabled camera, power adaptor and a swipeable interface to enhance user interaction. The objectives of the paper include designing a comprehensive smart mirror using CAD, integrating gesture control technology through Python's OpenCV package, constructing a functional prototype utilizing the Magic Mirror software, and conducting extensive testing. Key tests conducted include usability test to assess user interaction, functionality test to validate gesture control and mirror operations, data analysis for performance metrics, and visibility test for optimal display quality. Functionality test showed an average gesture detection accuracy of 92.5%, with the swipe left and swipe right gestures achieving the highest accuracy. In the usability test, the average response time across all gestures was 0.75 seconds, which is within the acceptable range for real-time interaction. Other performance indicators like error rate, average user satisfaction, device uptime and gesture latency were tested. These results demonstrated the effectiveness of the gesture-controlled interface, with the prototype showing high accuracy in gesture recognition and overall positive user feedback in terms of usability and reliability. The findings of this work suggest that the developed smart mirror could serve as a valuable addition to smart home environments, offering a seamless and interactive experience for users.

Application of Upper Bound Analysis and Taguchi Method In Aluminium Extrusion

Kamardeen Adebayo Ogunbajo — 2025-07-18

This research explores the use of upper bound analysis in calculating the extrusion force through u-shaped dies with varying fillet radii, billet lengths, friction coefficients and billet temperatures. Taguchi method was used in design of this experiment which is a four factor four level experiment giving a total of 16 experimental runs and aluminium 3003 was used as the workpiece. Based on these results a model equation was developed to predict the extrusion force. The correlation coefficient and covariance of the data generated, revealed that a positive and direct relationship existed between fillet radius, billet length, friction coefficient and extrusion force, while an inverse and indirect relationship existed between billet temperature and extrusion force. The R² value was 99.96% and adjusted R² value of 99.80% and a root mean square error of 0.2137, indicating that the accuracy of the model is good.

Investigation of Relationship between the Surface Roughness and Residual Stress on Pearlitic Ductile Iron Face Machined

Olutosin Olufisayo Ilori — 2025-07-18

This study investigates the relationship between surface roughness and residual stress in face-milled pearlitic ductile iron in order to enhance the surface quality of machined parts used in manufacturing. Locally prepared pearlitic ductile iron was utilized. The cutting factors that were explicitly taken into consideration in this study were cutting speed, depth of cut, fluid flow rate and feed rate. Taguchi's design served as the foundation for the experiment, which used an orthogonal array with five levels for each factor. The experimental data were statistically analyzed using correlation and multiple regression analyses. The findings show a substantial positive relationship (R = 0.938, p ≤ 0.01) between surface roughness and surface residual stress, which is statistically significant. The depth of cut and feed rate increased the surface residual stress by 511.212 and 0.668 units respectively, while a unit increase in cutting speed and fluid flow rate (-0.100 and -453.350 units respectively) decreased it. Likewise, the surface roughness increased by 53.958 and 0.063 units, respectively, with an increase in the depth of cut and feed rate. However, a unit increase in cutting speed and fluid flow rate resulted in a reduction in surface roughness (-0.003 and -21.132 units, respectively). It can be deduced from the multiple regression analysis that surface residual stress and surface roughness are associated with all cutting factors. These results can be used as a guide to improve the surface integrity of machined items. Thus, the study provided important information on the best cutting parameters for producing a significantly good surface finish during face milling operations in manufacturing industries.

Experimental Validation of Sustainable Aviation Fuel (SAF) Blending and Testing Methodologies for Small Turbofan Engine

Alex Ayedun Avwunuketa — 2025-07-21

Much research has been undertaken on the sustainable aviation fuels as the alternative to jet A-1 fuels due to magnitude demands of having carbon-free alternative fuel in the aviation industry. This study gives information on the combustion dynamics and emission performance of synthetic fuel blends of a small PTD 500 turbofan engine using a kinetically shaped reactivity model that is dependent on chemical kinetics and thermodynamics. Several blends of fuels containing different volumes of SAF content were created and tested on their conformance with ASTM D7566 and ASTM D4054 requirements. The experimental test of the engine measured thrust, fuel consumption and emissions over a range of operating conditions, reactivity model included activation energy and combustion kinetics to measure the dependence of fuel mass flow on exhaust gas forming Combustion behaviours was correlated to thrust output and CO and emissions by use of α 1 reactivity coefficient. In terms of the Take-off operation, the thrust contribution of engines ranged between 80%-90% but in idle operation, recorded 10%-15.As evident in the results, addition of SAF has insignificant impact on engine thrust gain, with significant impacts on combustion paths and routes related to the incomplete combustion formation. This was proved empirically as there was no difference in the consistency of the fuel blends and these differences in combustion chemistry were related to the change in the composition and calorific value of the hydrocarbons. The present research has established the compatibility of SAF with the existing engine systems and also the need to have a detailed kinetic model to optimize the use of fuel and reduce its environmental effects. The reactivity model is expected to be extended in future to include long-term engine operating conditions under typical SAF applications, which can be used to support the propulsion aviation sector transition to green propulsion.

Analysis of Nonlinear Control Strategies for Quadrotor Stability and Trajectory Tracking

Johnson Abiola — 2025-07-23

The quadrotor control as nonlinear and underactuated systems is a huge challenge in getting a fine stabilization and trajectory tracking. The present work seeks to introduce a novel hybrid control structure composed of an Internal Model Control-based Proportional-Integral (IMC-PI) controller, with the integration of a Sliding Mode Controller (SMC) and an Extended State Observer (ESO). The main purpose is to achieve improvement of stability and tracking performance under dynamic flight operations. A six degrees of freedom (6-DoF) dynamic model is developed under rigid body structure and proportional thrust-drag assumptions. An IMC-PI controller is initially employed to stabilize the Euler angles and vertical position but is not able to control the lateral positions (x and y). For this, a hybrid SMC-ESO method is incorporated for enhanced robustness along with precise path tracking. Simulation results reveal that while the stand-alone IMC-PI controller can stabilize altitude and orientation within 3 seconds, it cannot converge to the complete position. Nevertheless, the hybrid controller achieves very precise moving in complex trajectories (helical and figure-eight) within 25 seconds, which outperforms the stand-alone solution. The results confirm the viability of the hybrid controller in autonomous UAV operations where stability and precision are of particular importance.

Investigation of Thermal Behaviour of Mesocarp Fibre and Bituminous Coal with their Blends

Olutosin Olufisayo Ilori — 2025-07-23

In this study, an investigation was carried out on the thermal behaviour of mesocarp fibre, bituminous coal and their blends through dynamic thermogravimetric analysis. The analysis was carried out using 100% percentage composition of mesocarp fibre and bituminous coal respectively, and their blends (75, 50, and 25 wt% of mesocarp fibre, which implied 25, 50 and 75 wt% of coal). Two different heating rates were employed and pyrolysis temperature was between 30 through 900 ^oC. Three different thermal stages were identified from the DTG curve, and the mass loss during the first stage was attributed to the release of moisture still contained in the feedstock material. The decomposition intensity of MF was higher than that of CF for 5 ^oC/min while for 10 ^oC/min, the decomposition intensity of CF was substantially higher than that of MF for 100% MF and 100% CF by weight. For 5 ^oC/min, as the percentage by mass of CF increased in the sample, the initial temperature increased and final temperature decreased for stage 2 of the thermal stages, which was accompanied by a gradual decrease in weight loss. Although, the blending of MF with CF was found to have significant effects on the thermal behaviour of both feedstocks, due to a better pattern in the feedstocks’ behaviour at 5 ^oC/min heating rate, it can be deduced that this rate helps to have a better insight into the thermal behaviour of the feedstocks studied.

Communication as a Panacea for Resolving Crises in Energy Industry: The Case of Ikeja Electricity Distribution Company

Olawale Olaniyi Emmanuel Ajibola — 2025-07-25

Communication is the process by which people exchange information through a common set of symbols. It is appropriate to describe modern society as a knowledge society, in which ideas and information enabled by engineering are highly valued and knowledge has a big impact on the development process, including engineering education. However, the key to acquisition of knowledge is communication, thus the importance of communication in any ecosystem cannot be overemphasized; it is the life upon which an institution derives its existence. Without adequate communication, goals and aspiration of an organization will be difficult to achieve. The purpose of this research study which targets Ikeja Electricity Distribution Company (IKEDC) is to re-emphasize the importance of communication in resolving crisis, most especially in the energy sector where every effort made by the federal government of Nigeria to ensuring smooth delivery of uninterrupted supply of electricity for the consumption of hoi polloi to adequately facilitate engineering education. The results revealed that horizontal communication is an effective tool for crisis resolution. It also revealed that employees of IKEDC do not receive sufficient horizontal information to perform their duties successfully, and upward communication has not helped in resolving the energy issues. The study's objective is to ensure a steady power supply for the efficient operation of engineering education by encouraging the best possible use of IKEDC's current infrastructures through horizontal communication.

Optimizing the Impact and Yield Strengths of Cattle Horn for Engineering Applications

Kamoru Seidu — 2025-07-27

Cattle horns are one of wastes materials littering our environment, yet they have potential value in engineering. The work examined the engineering application of cow horn’s impact and yield strength. The physical and mechanical properties were examined to determine their levels of impacts and yield strengths. The horn structure contains keratin with lamellae tubules lapping over each other along the growing direction. The horn microstructures, density, water absorption, compression, flexural, hardness and impact test were examined. The samples have density of 1.303 g/cm³ to 1.376 g/cm³ along the body parts. The cow horns impact resiliencies vary along the parts due to animal maturity and ages. Cow horn withstands compressive stress and bending stress of 1,018.96 MPa and 981.4MPa respectively. The average values of hardness property for longitudinal and transverse are 51.735 N/mm² and 41.795 N/mm². The sustainability of the samples was analyzed using L₂₅ Taguchi orthogonal array by examining chemical compatibility, temperature and pressure as variable factors. The properties variations of the horns are attributed to the concentration of keratin substance along the body parts. The work identified an appropriates applications area using an impact and fatigue analysis which provided opportunities to use the material to produce sustainable engineering applications.

Improved Correlation of Oil Recovery Factor for Water Driven Reservoirs in the Niger Delta

Ayodele Daniel — 2025-07-29

Recovery factor is one of the most important variables for a reservoir engineer as it plays a major role in determining the economic viability of oil and gas projects and by implication what projects to mature. Over the years, many different approaches have been taken to estimating recovery factor of oil and gas reservoirs generally and these include simulations, volumetric method and correlations. All these methods have their high inherent cost except for correlations which are not only easy and quick to use but also low cost. Even though correlations have been developed in the past for the recovery factor of Niger Delta crude, none has employed the data analytics and machine learning techniques. Data from strong water driven crude oil reservoir in the Niger Delta was used in this study. After data cleaning and quality checking, cleaned data was used to train the machine learning model using multiple linear regression algorithms optimized with batch gradient descent method. This was implemented using Python code developed for this work. The model developed had an excellent performance on the training set as the coefficient was about 0.84. The mean absolute error is about 0.018. The results obtained showed better model performance and generalization than any previously existing model.

Drivers’ Information and Practical Training Assessment Results Management System: A Recommendation for NIT

Deogratias Tasilo Mahuwi — 2025-07-30

Road Traffic Injuries (RTIs) resulted from Road Traffic Accidents (RTAs) have high contribution to human deaths globally where in 2023, 1733 RTAs which resulted into 1647 deaths were recorded in Tanzania with human factor contributing 97% of the RTAs. The situation has raised a need to conduct a study to identify how drivers training processes are handled in Tanzania. The National Institute of Transport (NIT) was selected for the study to present the current situation since it is the institute offering training to the professional drivers and drivers’ instructors in Tanzania. In-car, Automated, Simulator-based, Structured Off-Road and Clinical Drivers’ Assessments were identified in the literature as the common methods for assessing the drivers’ practical skills. Interview was used to collect data from the targeted personnel who were identified as Director of Academics Support Services (DASS), Head of Department (HoD) for driving courses and National Institute of Transport Certified Driver Instructors (NIT-CDIs). The research findings highlighted issues in the process of drivers’ registration, record keeping and backup, assessment methods, result verification, analysis and reporting. The study has recommended algorithms in some crucial aspects of the drivers’ trainings that could be used to improve the standard of the drivers’ training processes which could ultimately contribute to the reduction of RTAs and RTIs in Tanzania and globally. Further researches are needed to study the driver training processes in other institutes in Tanzania and recommend better, affordable and more effective approaches for handling drivers’ trainings.

Development of an Open Hearth Furnace with a Mechanical Blower and Mechanized Bellow

Oluwasanmi Iyiola Alonge — 2025-07-31

This study focuses on the development of a hearth furnace with a mechanical blower and mechanized bellow intended to replace traditional open-hearth furnaces with restricted operational efficiency. The bellow system utilizes a crank-slider mechanism powered by an electric motor to generate a continuous airflow, thereby optimizing combustion within the furnace. The total force acting on the crank-slider was 22.22 N, and the calculated stoichiometric air required for complete combustion of the charcoal was 26.80 . The maximum temperature recorded during performance evaluation was 110 5 for the blower with energy consumption of 940.8 kJ and 923.9 for the bellow with energy consumption of 24.4 kJ. The air speed achieved by the bellow was 3.5 m/s each time the bellow compresses, with reduced pulsating interval and enhanced combustion of the charcoal. Compared to manual operation, the furnace reduced human exposure to heat, eliminated operational fatigue, and improved the overall efficiency and safety of the furnace operation. The results demonstrate that integrating a mechanical blower and a mechanized bellow into open-hearth furnace systems is a viable method to boost production rates and occupational safety in small-scale foundry operations.

Effect of Heat Treatment on Microstructure, Acidic Corrosion Resistance and Wear Performance of Low-Carbon Steel

Basiru Philip Aramide — 2025-07-31

Low-carbon steels are widely used in structural and industrial applications, but their performance can be significantly enhanced through controlled thermal processing. This paper looks at how different heat treatment techniques affect low-carbon steel's microstructure, corrosion resistance in acidic settings, and wear performance. Mechanical and electrochemical behaviours were evaluated under four heat treatment conditions: normalizing (A), water quenching (Q), normalizing followed by quenching (AQ), and double (cyclic) quenching (QQ). Phase changes were characterized by optical microscopy; Vickers microhardness testing and depth profiling evaluated hardness distribution. Using linear polarization techniques, electrochemical corrosion tests in dilute sulfuric acid (H₂SO₄) were run to find corrosion potential, current density, and polarization resistance. Using a pin-on-disc apparatus, wear performance was also assessed under 10 N and 20 N loads. Results revealed that quenching greatly increased surface hardness because of martensite formation; Q had the highest microhardness but lower corrosion resistance because of microstructural stress and heterogeneity. By contrast, AQ offered a balanced microstructure with fair hardness and excellent corrosion resistance. Wear rates were closely connected to hardness; QQ showed the greatest wear resistance at both load conditions. These results highlight the importance of heat treatment in maximizing the surface integrity of carbon steel for uses in mechanically hostile and acidic environments.