Nigerian Journal of Technological Development
The Nigerian Journal of Technological Development is a quarterly publication of the Faculty of Engineering & Technology, University of Ilorin, Ilorin, Nigeria. It publishes original high-quality articles focusing on all aspects of Engineering and Applied Sciences. Manuscripts are double-blind peer-reviewed and if found suitable, published according to the subject matter as a Research Paper, Review Paper or a Technical Note. It is indexed by AJOL, Scopus, Google Scholar, and DOAJ.
Faculty of Engineering and Technology, University of Ilorin, Nigeria.
In accordance with the Copyright Act of 1976, which became effective January 1, 1978, the following statement signed by each author must accompany the manuscript submitted: "I, the undersigned author, transfer all copyright ownership of the manuscript referenced above to the Nigerian Journal of Technological Development, in the event the work is published. I warrant that the article is original, does not infringe upon any copyright or other proprietary right of any third party, is not under consideration by another journal, and has not been published previously. I have reviewed and approved the submitted version of the manuscript and agree to its publication in the Nigerian Journal of Technological Development." A copyright transfer form can be downloaded from the NJTD Website (http://njtd.com.ng/index.php/njtd). Author(s) will be consulted, whenever possible, regarding republication of material. All authors must have access to the data presented, and the authors and sponsor (if applicable) must agree to share original data with the editor if requested.
Investigation of Quality and Heavy Metal Pollution in Vegetable-Growing Areas of Ogun and Oyo States, Nigeria
Anthropogenic activities cause soil pollution. The study assessed soil quality and heavy metal pollution in vegetable growing areas of Ogun and Oyo states, Nigeria. Samples were collected at 3 points to form composite sample of 500 g collected from 11 selected farm settlement areas in replicates. The concentrations of physicochemical parameters, including selected heavy metals {Copper (Cu), Chromium (Cr), Nickel (Ni), Lead (Pb) and Cadmium (Cd)}, were analyzed. The Soil Indices were assessed. The soils were of Na2SO4 type, and with pH exceeding the limit for vegetable cultivation, except in Odogbolu and Kisi. The Na2SO4 content in soil may reduce the limit of soil moisture, thereby having negative impacts on soil strength with consequence on plant yield. There were significant (p < 0.05) variations in all parameters analyzed, with the majority exceeding acceptable limits. The concentration of metals decreased in the order of Cu > Pb > Cd. > Cr > Ni. Cu was in abundance in all samples. The Pb and Cd levels in the majority of samples exceeded the regulatory standard. Iresa has the greatest soil quality index values (0.69) and scores indicating no limitations to soil pollution. Soils were moderately polluted with Cu and Pb, with the highest detected in Ilaro in Ogun state and Ido in Oyo state. Regulatory authorities should provide effective controls to reduce Cu and Pb pollution in these study areas.
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Investigation on Dynamic Performance of Aluminium – Steel Composite Foam based Redundant SCARA Robot
This research examines the effects of foam made of aluminium alloy low carbon (Al-LC) steel on the joint dynamics of Redundant Selective Compliance Articulated Robot Arm (RSCARA). When building a SolidWorks CAD model that incorporates MATLAB/Simscape Multibody, RSCARA components are designed using a customized composite foam material. The dynamic property torque generated at robot joints is determined by simulating the RSCARA system blocks technique using the Simscape Multibody System (SMBS). The use of Aluminium-Low Carbon Composite Metal Foam (AL-LC CMF) in the evolution of RSCARA was shown to be relevant by the dynamic property observations based on the Simscape simulation results.
Copyright (c) 2025 Nigerian Journal of Technological Development http://creativecommons.org/licenses/by-nc-sa/4.0
Advancing Process Intensification in Petrochemical and Specialty Chemical Manufacturing – A Mini Review
The chemical process industries face increasing pressure to improve efficiency and reduce environmental impact. Process intensification (PI) has emerged as a top strategy to achieve step-change improvements in performance and sustainability by fundamentally reimagining process design. PI involves radically redesigning processes and equipment to integrate functions, boost transfer rates, and eliminate inefficiencies, thereby shrinking the footprint of operations while improving energy and material utilisation. Researchers have touted PI as “the most promising way to achieve sustainable development” in sectors like oil and gas. This approach promises cleaner, smaller, and more efficient processes that meet economic and environmental objectives simultaneously. However, despite many novel PI technologies reported in the literature, relatively few have seen broad commercial adoption in petrochemical and chemical plants so far. Bridging this gap through practical design methodologies and demonstrated industrial successes is a critical challenge. This review discusses key process intensification strategies (integrated unit operations, advanced distillation technologies, novel reactors, membrane systems, and modular processing) and how they are transforming petrochemical and speciality chemical manufacturing. It also examines the benefits achieved through PI and the challenges that must be overcome to fully realise its potential.
Grid Protection through Optimal Overcurrent Relay Coordination using Hybrid FA-PSO Technique
The optimal coordination of OCRs (Overcurrent Relays) is vital for guaranteeing the dependable and efficient operation of electricity grids. The increasing complexity of these grids, characterized by diverse fault currents, system configurations, and operating conditions, pose significant challenge to relay coordination (RC). In this study, a novel optimization framework is proposed, FA (Firefly Algorithm) and PSO (Particle Swarm Optimization) techniques were integrated to determine optimal relay settings. The outcomes prove that the proposed hybrid approach ensures optimal RC and thus, minimizes the risk of false tripping. Lower time multiplier settings and relay operating time was achieved in both IEEE three-bus and six-bus systems, and satisfactory CTI (Coordination Time Interval) of backup and primary relays was also achieved. For instance, an average CTI of 0.265s was achieved with FA-PSO, while CTI of 0.308s and 0.290s was attained with FA and PSO techniques for the 3-bus system. This work will aid in the growth of efficient and reliable power grid protection systems, ensuring a stable and secure supply of electricity. The utilized approach is applicable to various grid configurations and can be integrated with existing grid management systems.
Application of Six Sigma DMADV Methodology Approach for Improving Concrete Masonry Mixing Process
The poor quality of concrete masonry, which is frequently caused by irregular material composition and inefficient manufacturing processes, has been linked to building collapses in Nigeria. The Six Sigma DMADV (Define, Measure, Analyse, Design, Verify) methodology is used in this paper to improve the concrete masonry mixing procedure. The study takes on a case study design to identify the process deficiencies, which leads to the development of a mechanised mixing system to improve the masonry aggregates. Finite Element Analysis (FEA) optimises the new concrete block designs to reduce weight and maintain structural integrity and ergonomic efficiency. The results show that implementing the Six Sigma DMADV improves manufacturing quality, reduces defects, and ensures consistency in concrete masonry manufacturing. Among the 12 model samples produced by the FEA for the new concrete masonry machine design, model L is the most optimal, with volume, weight, stress, and the factor of safety measuring 364440 mm3, 8.773 kg, 5.271 MPa, and 1.01, respectively. The paper concludes that the integration of systematic quality control measures as well as automation in the production of small and medium-scale concrete can reduce construction failures, leading to safer and more durable buildings.
Assessment of the Effect of Night-time Lighting on Crime Incidence in University Campus Using GIS Technique
In recent years, University campuses have grown more diverse throughout Nigeria; however, with attendant security challenges. This study investigates the relationship between crime and nighttime illumination in the University of Ilorin Campus using GIS techniques. Geospatial datasets including the road network, buildings, illumination sources (street lights), and location of historical crime spots were collected and converted into a geodatabase for analysis. First, average nearest neighborhood (ANN), point density (PD), and kernel density point analysis were applied to determine the distribution pattern and nighttime lighting intensity. Subsequently, by overlaying the crime spots data layer and nighttime illumination map, the relationship between them was determined using percentage of agreement statistics. Analysis of the spatial distribution of streetlights indicates a clustered pattern with an ANN value of 0.575 and a Z-score of -23.131. Also, statistical evaluation has shown that almost 70% of crimes occurred in poorly illuminated areas, under the cover of darkness. The findings highlight a critical intersection between public safety and urban planning at the University of Ilorin. By addressing the challenges posed by inadequate lighting through public power supply, the university can enhance security, foster a vibrant campus life, and reduce crime rates. Investing in reliable and sustainable lighting solutions promotes safety and contributes to the overall well-being of the campus community.
Numerical Simulation of Floating-Production, Storage, and Offloading System Mooring Dynamics: A Simplified Methodology
This study presents a simplified methodology designed to enhance efficiency and clarity by minimizing procedural complexity without compromising the accuracy and reliability of outcomes. Marine cable systems face operational challenges due to unresolved dynamic equations and quadratic hydrodynamic drag from environmental factors. The study applied numerical solutions to Mooring systems Dynamics validated against those from ANSYS. The hydrodynamic responses of the FPSO and its mooring system were analyzed. Results indicate that the system experiences dynamic loading, with tension forces in the mooring cable ranging from 188,873.27 N to 397,107.78 N. The mooring sum forces exhibit fluctuations, reaching a minimum of -78,858.34 N and a maximum of -31,710.57 N in the global X direction. The heave direction, forces ranged from -389,218.63 to -186,192.23 N. The study found that application of advanced meshing techniques, sensitivity analysis, and integration of real-time environmental data with advanced nonlinear dynamics, can address time-dependent problems in mooring systems to improved simulation-accuracy. This study contributes to the comprehensive understanding of mooring system dynamics, providing valuable insights into the design, operation, and safety of FPSOs in challenging marine environments.
Ballast Water Treatment Using Modified Cow-Dung and Plantain Peels NanoBiochars
Ballast water treatment is a crucial aspect of environmental protection, aiming to minimize the transfer of non-indigenous species. In this study, Biochar Klin pyrolyzer, was used to prepare the nanobiochars from cow-dung and plantain peels followed by ball-milling, and centrifugation. The nanobiochars were subjected to acidic and alkaline treatments and then characterized for their physico-chemical properties, as well as the ballast water using prescribed standard methods. The pre-treatment analysis of the ballast water sample revealed a pH of 9.2, chloride ion concentration of 68.7 mg/L (well below the WHO standard of 250 mg/L), nitrate concentration of 5.6 mg/L (above the WHO standard of 3.2 mg/L), and sulphate concentration of 3.2 mg/L (below the WHO standard of 250 mg/L). The BOD and COD levels were 28.6 mg/L and 54.2 mg/L, respectively, both significantly exceeding the WHO standard of 10 mg/L. Post-treatment examination revealed that the modified plantain peel biochar effectively reduced the concentration of pollutants( Lead (Pb2+) from 0.314mg/L to 0.104mg/L, Cadmium ( Cd2+) from 0.028mg/L to 0.025mg/L) and microbial organisms (coliforms from 2.1cfu/mL to 1.1cfu/mL) thereby demonstrating its potential as a sustainable and cost-effective treatment solution. Activated adsorbent's larger surface area and nanoporous structure significantly enhanced its adsorption capacity.
Modelling and Optimisation of Strength Performance in Self-Compacting Concrete Incorporating Cement Kiln Dust and Superplasticizer
The rising cost of construction materials and the growing demand for sustainability in Civil Engineering have encouraged the use of industrial byproducts as alternative materials. Cement kiln dust (CKD), a waste from cement production, poses environmental disposal challenges but can potentially enhance sustainable concrete production. This study aims to model and optimize the strength performance of self-compacting concrete (SCC) incorporating CKD and varying dosages of superplasticizer (SP) using response surface methodology (RSM). SCC mixes were prepared with CKD replacing cement at 0–25 % and SP dosages of 1.0–2.5 % by weight of cementitious materials, maintaining a water–cement ratio of 0.43 and a mix proportion of 1:2.44:1.48. Mechanical properties, which includes compressive, flexural, and split tensile strengths were evaluated. Multi-linear regression modelling was used for mathematical modelling. Incorporating CKD content reduced strength, whereas higher SP dosage improved both /;workability and mechanical performance. Optimum strengths of 26 N/mm² (compressive), 5.06 N/mm² (flexural), and 3.98 N/mm² (split tensile) were recorded at 10 % CKD and 2 % SP. Predictive models achieved high accuracy with R² values of 88.84 %, 95.36 %, and 94.68 %, respectively. Multi-parameter optimization revealed ideal conditions at 15 % CKD, 2 % SP, and 46 days of curing. CKD can serve as a sustainable supplementary material in SCC, reducing environmental impact and construction costs. For best performance, CKD should be limited to around 10–15 % with 2 % SP dosage.
Development of a Smart Dual-Energy Crop Dryer with Heat Recovery Integration: Zero-Load Thermal Dynamics Test Validation
Innovative drying strategies are essential to the advancement of sustainable postharvest processing. This work presents the development and zero-load thermal characterization test of a smart dual-energy crop dryer integrated with a heat recovery unit. To improve thermal stability and energy efficiency, the dryer incorporates an Arduino-based control unit, solar and electric heating, and heat recovery. According to test data, the solar collector maintained a 38 to 45% thermal gain over ambient conditions and a 40.9% temperature increase in the drying air while reaching temperatures of up to 65°C. It exhibited a remarkable thermal efficiency of 80.76%. The dryer adaptively consumed 74.1% electric and 25.9% solar energy, guaranteeing a steady heat supply during variable solar radiation. A heat-up time of 6.2 to 12 minutes was recorded, with the best performance occurring between 55 °C and 60°C and 1.5 m/s and 2.0 m/s of air velocity. The dryer’s heat-up behaviours were successfully predicted by a fitted quadratic model (R² = 0.9585). The exhaust heat recovery system reduced energy loss and improved the moisture extraction effectiveness by providing low-humidity preheated air. These results demonstrate the dryer's fast response time, energy flexibility, and appropriateness for off-grid crop drying.
A Hybrid FEA and MOGA-Based Optimization Framework for Industrial Switched Reluctance Motors
Switched Reluctance Motors (SRMs) are increasingly used in industrial drives and electric vehicles due to their robust construction, fault tolerance, and wide speed range. However, the non-linear magnetic characteristics of SRMs often lead to torque ripple, vibration, and acoustic noise, posing challenges to achieving optimal performance. This paper presents a Hybrid Finite Element Analysis (FEA) and Multi-Objective Genetic Algorithm (MOGA)-based optimization framework for the industrial design of SRMs. The proposed method integrates accurate electromagnetic simulation using FEA with the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) to optimize key geometric parameters, stator pole arc ratio (Es), rotor pole arc ratio (Er), and stator yoke height (Ys), under multiple objectives and design constraints. The objectives are to maximize average torque and efficiency while minimizing torque ripple and total power loss. Constraints on torque, current density, and temperature are incorporated to ensure thermal and electromagnetic feasibility. Compared with conventional single-objective and unconstrained multi-objective SRM designs, the proposed framework offers a clearly interpretable and reproducible optimization route. It achieves a 71.5 % increase in average torque and reduces torque ripple to 3.18% while satisfying electromagnetic and thermal constraints. The framework’s novelty lies in integrating a robust FEA-based evaluation loop with constrained multi-objective decision-making, enabling industrial designers to identify balanced, high-performance SRM geometries efficiently. Future work includes experimental prototyping and machine learning integration to further enhance optimization efficiency.
An Integrated Simulink and Iot Framework for Data Acquisition and Control using Custom Driver Blocks
This study deals with the design and implementation of a fully modularized, embedded system equipped with Internet of Things (IoT) technology, which is developed in the Simulink integrated control. A key contribution of the work is the utilization of the Simulink environment only to conduct object-oriented models without the use of the traditional script-based programming methods. It describes a combination of extensive integration of custom driver blocks through supplementary libraries and S-function algorithm development combined with sensor reading calibration and filtering that further extends the flexibility of the workflow. The performance of the system was validated by creating a real-time data acquisition, on/off control logic, and cloud-based data visualization through ThingSpeak platform, demonstrated by a case study of an irrigation system in an arid area. The system is versatile, as it is modular and can be adapted to embedded systems in arid, resource-constrained regions, making it suitable for applications in intelligent control and automation in many other applications beyond irrigation.
System Identification Modelling for Humidity Control in a Centralised Water-Cooled Package Unit Air Conditioning System
In humid countries like Malaysia, there is a need to take more cognisance of the control of humidity, as this significantly affects the thermal comfort and health of the occupants. Effective control mechanisms in HVAC systems also assist in regulating energy consumption, as HVAC is the major consumer of energy in the building sector. Intelligent control systems require accurate models that capture the system’s dynamics. This study utilises the system identification technique for a multi-circuit centralised water-cooled air-conditioning system in the model development and selection for the control of humidity in the system. Several models, including Box-Jenkins, State Space, Output-Error, Autoregressive with External Input, and Autoregressive-Moving Average with External Input, were estimated and evaluated. The outcome revealed that the Box-Jenkins third-order model gave the overall best fit with a value of 93.56%, the lowest Final Prediction Error with a value of 0.2016, and the lowest Mean Square Error with a value of 0.1978.
Sodium Nitrate Flooding Concentrations on the Petrographic and Geomechanical Properties of Sandstone Reservoir Rocks
The geochemistry and geomechanical characteristics of the reservoir formation can be negatively impacted by fluid flow and fluid-rock interactions. Chemical-rock interaction in the oilfield happens during water injection, chemical flooding, and inhibitor use; the degree of interaction varies with concentration and could impact the rock's petrographic and geomechanical properties. Sodium nitrate (NaNO3) is used to modulate reservoir souring caused by sulphate-reducing bacteria (SRB) during waterflooding. This study investigates how NaNO3 alters sandstone properties at 637.5, 850, 1062.4, and 1275 ppm via core flooding, using Uniaxial Compressive Strength (UCS), Particle Size Distribution (PSD), Scanning Electron Microscopy (SEM) with Energy-Dispersive X-ray spectroscopy (EDX), and X-Ray Powder Diffraction (XRPD) analyses to assess nitrate flooding effects. The findings showed that at sodium nitrate concentrations less than 850 ppm, only minor changes in PSD appeared, whereas at higher concentrations, the particle size distribution changed significantly. Furthermore, SEM/EDX and XRPD results indicated elemental and mineralogical changes, suggesting that the rock-NaNO3 interactions resulted in the dissolution and precipitation of minerals as well as phase transformation. As the sodium nitrate concentration increased from 850 ppm to 1062.4 ppm, the sandstone's permeability and porosity increased significantly from 69±1.2 mD and 12±2.4% to 81±0.4 mD and 20±8% mD, respectively. Thus, at higher NaNO3 concentrations (> 850 ppm), a significant reduction of the UCS of sandstone was observed. Overall, these findings highlight the significant risk posed by higher concentrations of sodium nitrate under dynamic conditions in oilfields, underscoring the need for optimized chemical formulation to prevent reservoir formation damage and operational challenges.
Contract-Oriented Optimal Economic Dispatch of Thermal Generators in a Multi-Area Deregulated Power System
Bilateral contract between the Distribution Companies (DISCOs) and Generation Companies (GENCOs), modelled using DISCO Participation Matrix (DPM), has significant impact on the economic scheduling scheme of thermal generators in Multi-Area Power Systems (MAPS). Neglecting the contract while formulating the scheme can results in suboptimal solutions and inefficient utilization of resources. Thus, this paper proposed a DPM-constrained optimal Economic Dispatch (ED) scheme for multi-fuel type thermal generators in MAPS. The ED scheme minimized the fuel cost of the generators of each GENCO subject to the DPM, generation-demand balance, generation limits, and line transmission capacity as constraints. Due to its fast convergence, flexibility and global optimum searching mechanism, Cuckoo Search Algorithm (CSA) is used to solve the ED problem. The developed scheme is implemented on IEEE 39-bus and 52-bus Nigerian Power System (NPS) both partitioned into three CAs with multiple DISCOs and GENCOs. The effectiveness of the scheme is evaluated by simulating the systems in MATLAB environment. The performance of the ED on the IEEE 39-bus is evaluated by comparing it with those obtained using Grey Wolf Optimizer (MOGWO). It is observed that the fuel cost is reduced by 22.34%, from 5.655×106$/h obtained using the MOGWO to 4.392×106$/h with the developed CSA-based ED schemes. This signifies a substantial improvement over the MOGWO-based solution. Likewise, the ED scheme’s performance on NPS is evaluated by comparing its performance with that obtained using Bat Algorithm (BA). For the 24-hour ED on the NPS, the fuel cost is reduced from 2.467×106$/h to 1.953×106$/h, representing 20.85% reduction. These cost reductions emphasize the significance of imposing the DPM constraint as well as the superior optimization capability of the CSA algorithm in generating schedules that minimize fuel costs compared to the MOGWO and BA-based methods.
Understanding E-Health Implementation in the Democratic Republic of the Congo: A Systematic Literature Review
The Democratic Republic of the Congo (DRC) faces an abysmal health system comprising lack of access, extreme shortage of healthcare workers, and?high disease burden. The use of information and?communication technologies (ICTs) in health (e-health) is a potential solution to these challenges. This systematic literature review synthesizes existing evidence surrounding e-health in the Democratic Republic of the Congo and explores the?success and challenges faced during the implementation as well as the perceived potential of e-health in this complex environment. This study is a?systematic review aimed at investigating and evaluating the literature on e-health implementation in DRC. The study finds that, although?e-health provides great potential, its uptake. problems associated with infrastructure, human resources, funding, policy, and sociocultural?factors are still developing. This paper presents the findings, highlighting key trends, challenges, and opportunities, and offering recommendations for practitioners and researchers to accelerate the effective and sustainable integration of e-health into the DRC's healthcare system.
Enhancing Microbial Activity with Rotten Rice Flour to Facilitate Heavy Metal Remediation and Bioenergy Generation via Microbial Fuel Cell
Microbial fuel cells (MFCs) have emerged as an innovative approach to addressing environmental pollutants while producing renewable energy. The selection of appropriate substrates plays a pivotal role in fostering microorganism growth and enhancing bioremediation. This study explores the incorporation of rotten rice flour (RRF) as a substrate in MFCs, evaluating its impact on microbial metabolism, bioenergy generation, and bioremediation of toxic metals. The MFC process, lasting 37 days, produced a peak voltage output of 200 mV on day 21 demonstrating the potential of RRF as a sustainable and effective substrate for microbial growth and bioenergy generation. The MFC cycle generates final bioremediation efficiencies of 83.78%, 85.44%, 87.10% for Al3+; 85.54 %, 87.54, 88.90 for Cu2+ and 87.00%, 90.92%, 93.34% for Pb2+respectively indicating its potential in ameliorating toxic metal levels. The organic substrate, rotten rice flour was applied to the anodic region daily throughout the experiment. Furthermore, bacteria analysis was investigated on the anode electrode after MFC operation which revealed the presence of Staphylococcus aureus, Escherichia coli, Serratia sp. and Bacillus sp. respectively. The findings suggested that rotten rice flour could serve as an effective organic substrate for applications involving MFC. Furthermore, this research sheds light on the existing prospects of MFC technology and proposes insightful recommendations for its future development.
Power Performance Analysis in Off-Grid Photovoltaic Battery System with ANFIS-FL Based MPPT Under Partial Shading Effects
Photovoltaic (PV) systems combined with battery storage offer a reliable and autonomous energy solution for isolated regions. However, ensuring an optimal energy balance between production and consumption, while maintaining system stability under variable solar irradiation, remains a significant challenge. Therefore, the study proposes an all-encompassing control system for off-grid photovoltaic (PV) systems. The approach considers an MPPT algorithm with adaptive neuro-fuzzy inference system (ANFIS) and fuzzy logic (FL) as the controller, which would maximize energy extraction from photovoltaic panels subjected to partial shading conditions. The system also includes a DC-AC inverter with vector control to maintain the DC bus voltage at 800 V, together with a battery management algorithm to supervise battery charging and discharging. Energy dissipation is also incorporated to balance excess production. The system's performance was simulated and evaluated using two constant loads: 35 kW and 40 kW. Results highlight a critical operational distinction: while the 40 kW scenario was fully managed by the battery storage capabilities, the 35 kW scenario required the active intervention of the dissipation system to evacuate excess power and maintain DC bus stability. Simulation results demonstrate that the proposed ANFIS-FL controller achieves a rapid MPPT response time of 0.05 s, successfully tracking the Global Maximum Power Point (GMPP) under dynamic partial shading without steady-state oscillations. Regarding stability, the DC bus voltage was tightly regulated at 800 V, with transient overshoots limited to 6.25% and 9% under the 35 kW and 40 kW scenarios, respectively.
Underwater Data Centres – Innovative Computing Solutions for Stowing Servers in Ocean Computing Platforms to Reduce Deployment Costs
The siting of data centres comprising multiple server racks in an underwater environment is recognized to reduce cooling costs and improve datacentre performance. However, the siting of data centres in the ocean raises new deployment challenges for cloud service providers. The deployment of large sized datacentres in an underwater environment requires purchasing or hiring large sized high capacity ocean vessels that transport underwater data centres to the designated underwater location before it is dunked into the ocean. The hiring of high capacity ocean vessels with high costs is challenging for cloud service providers with small capital resources. The intended hire might not be challenging for cloud service providers such as Amazon, Google, and Microsoft with significant capital resources. In addition, the use of high capacity ocean vessels increases the visibility of the locations of underwater data centre to other actors leveraging on the ocean’s resources for other applications. The use of small capacity ocean vessels reduces the visibility thereby enhancing the security of the underwater data centre. The research being proposed presents a computing based furling and stowing solution. The proposed solution varies the dimensions of server chassis within pre – defined minimum and maximum values. It realizes the goal by incorporating the computing framework and an enabling architecture.
Toward the Improvement of Port Construction in African Bays : A Literature Review of Scientific Advances on the Seismic Stability of Rubble Mound Breakwaters
The progressive integration of African port infrastructures into global maritime networks underscores the strategic importance of ensuring the seismic stability of coastal engineering structures that support resource exports and economic development. This review synthesizes current knowledge on rubble-mound breakwaters, emphasizing their behavior and stability under seismic loading. It examines documented damages to ports and breakwaters during major earthquakes and analyzes empirical data and case studies illustrating the impact of seismic loads on these structures. The paper also reviews experimental, numerical, and analytical approaches used to assess breakwater stability and explores reinforcement strategies aimed at improving seismic resilience. Overall, this study provides a comprehensive overview of the damages and advances in enhancing the performance of rubble-mound breakwaters under seismic conditions, offering valuable insights for engineers and researchers in structural engineering.
Numerical and Semi-empirical Prediction of Zero-Lift Drag Coefficient of a Small Caliber Spinning Projectile: A Comparative Investigation
This paper focuses on a comparative performance evaluation of the numerical and semi-empirical methods in predicting the zero-lift drag of a generic spinning projectile, namely, the 5.69mm BRL-1 projectile. The numerical simulations of the flow around the projectile were conducted using Reynolds-Averaged Navier-Stokes equations with Shear Stress Transport k-ω turbulence model. The simulation results were validated comparing against existing experimental data. The McCoy method was applied for semi-empirical prediction of zero-lift drag of the projectile. The pressure drag, skin friction drag and base drag components of the total aerodynamic drag of the projectile at various Mach numbers were also investigated in this study. The aerodynamic drags obtained using numerical and semi-empirical methods were compared to show strengths and shortcomings of each approach. The average difference between numerical and experimental zero-lift drag coefficients is 1.74%, while the corresponding value for semi-empirical and experimental zero-lift drag coefficients is 5.31%.
Tribological And Corrosion Resistance of Food Grinding Discs: Effects of Ferrochromium
The pervasive use of cast-iron grinding discs in domestic food preparation poses a dual challenge of material degradation and food safety risks due to tribo-corrosive wear. This study presents the effects of ferrochromium tribological and corrosion resistance of food grinding discs. The study examined a sustainable solution by engineering high-performance, chromium-alloyed grinding discs from upcycled Toyota Engine Block (TEB) scrap. The influences of varying Fe-Cr additions on the microstructure, mechanical properties, and corrosion resistance of the resultant cast irons, which were normalized at 650°C and 850°C were systematically investigated. A comprehensive suite of characterization techniques, including hardness, tensile, wear, and impact testing, supplemented by SEM-EDS, XRF, and XRD analysis, reveals that chromium addition facilitates the formation of protective carbides and a stable passive layer. The results demonstrated a significant enhancement in performance: hardness and yield strength increase substantially, leading to a marked reduction in wear rate and a profound inhibition of corrosion susceptibility, as quantified by gasometric and potentiodynamic polarization methods. This work establishes a robust pathway for transforming industrial waste into superior, food-safe components, with direct implications for enhancing product longevity, reducing environmental footprint, and mitigating contamination risks in consumer appliances.
Augmented Unscented Kalman Filter-Based Method for Voltage Sag Detection and Characterization
This paper proposes a new method for the detection and characterization of voltage sag events in power systems. The proposed method uses the numerical simulation results of an augmented unscented Kalman filter (AUKF) to estimate the voltage sag waveform. The AUKF does not compute the Jacobian matrices, therefore, it offers significant computational advantages over the extended Kalman filter. Additionally, the proposed algorithm uses the residual sequence from the AUKF to detect and estimate the time-related parameters of voltage sag events, and the estimated fundamental magnitude is used to compute the voltage magnitude during the event. The effectiveness of the AUKF method is confirmed in this work via the numerical simulation results of voltage sag waveforms with and without harmonics.
Genetic Mapping and Marker-Assisted Selection for Late Leaf Spot Resistance in Arachis hypogaea L.
Late leaf spot (LLS), caused by Nothopassalora personata, poses a significant threat to global groundnut (Arachis hypogaea) production, causing severe yield losses and increased reliance on costly fungicides. This study focuses on improving LLS resistance in groundnut genotypes through genetic mapping and marker-assisted selection (MAS). Twenty diverse genotypes, including local landraces and improved varieties, were evaluated for LLS resistance and pod yield across three Nigerian States. Disease severity was scored on a 1-9 scale, and SSR and SNP markers provided genotypic data. QTL mapping identified three significant QTLs on Chromosomes 2, 5, and 9, with the major QTL, qLLS1, explaining 38% of the phenotypic variance. High broad-sense heritability estimates for LLS severity (0.72) and pod yield (0.68) indicate strong genetic control. A significant negative correlation (r = -0.65, p < 0.01) between LLS severity and pod yield underscores the potential yield benefits of resistance breeding. The identified QTLs, especially qLLS1, provide valuable markers for MAS, facilitating the efficient selection of resistant genotypes. These findings support the development of LLS-resistant cultivars, promoting sustainable groundnut production and food security.
Integrating Large-Scale Variable Renewable Energy Resources on the Transmission Grid: A Case Study of the Nigerian Transmission System
A more sustainable energy mix is the purpose of the global energy transition, which aims to minimize the energy sector's dependence on fossil fuels. To provide sustainable and reliable energy generation and to evaluate grid stability, it is critical to estimate the level of renewable energy penetration in power grids. In this work, an overview of solar and wind energy potential in Nigeria was assessed. The Nigerian transmission power system was simulated using DIgSILENT PowerFactory software. There were 48 buses in the modelled 330 kV network, which was simulated under normal operating conditions for a simulation time of 15 seconds. The simulation considered four scenarios: the base case, 10%, 20%, and 30% wind and solar penetration. The effect of increasing the variable renewable energy sources was observed in the voltage profile as well as the frequency of the grid. Frequency was lowest in the scenario with 30% variable renewable integration, which was not within the normal operating range, this was due to higher portion of variable renewable energy in the network. The voltage profile of 10% and 20% renewable penetration levels showed some buses that exceeded the set limits which would cause voltage instability in the system. Results highlight the importance of ensuring voltage and frequency stability across the system, especially as the renewable energy penetration increases. Also, results suggest the need for additional control strategies, to guarantee stability in the power system.
Design and Simulation of Locust Beans (Parkia Biglobosa) Processing Plant
African locust beans (Parkia biglobosa) have a rich nutritional content and distinctive flavour, which makes it useful as a food condiment. However, its traditional processing is inefficient and labour-intensive. Hence, this study aims to design and simulate a locust bean processing plant to address challenges posed by conventional methods of locust bean production, including low production, poor packaging, seed degradation, and waste. By designing and modelling components of a processing plant using SolidWorks 2016, the study sought to modernise locust bean production techniques and create a high-quality product that can compete with other food condiments. The plant is designed to have a throughput capacity of 250 kg/hr, with the cubing blade containing 10 square cubing holes, each 20 mm × 20 mm in cross section. The finite element analysis (FEA) technique and the Von Mises stress criterion were employed to assess the structural stability of the plant’s components against the functional requirements. The simulation results show that the various stresses induced in the components were below the yield strength of the selected materials, with minimal strain and displacement, and a factor of safety greater than 1. This implies that the various components will likely meet the service requirements without failing under normal operating conditions. This study presents empirical data that can help improve the design of locust bean production plants to promote high-quality production.
Marine Corrosion Mitigation of Mild Steel in Simulated Sea Water by Leaf Extract of Barteria Fistulosa
Carbon steel is one of the major materials used in the construction of sea piers as well as oil and gas transit pipes. The corrosion of undersea oil and gas pipelines often lead to leakages which result in financial losses and irreparable damage to marine lives. This study investigated the use of Barteria fistulosa (BF) leaves extract as a non-toxic corrosion inhibitor of low carbon steel in 3.5% NaCl employing weight loss method, potentiodynamic polarization (PDP) and electrochemical impedance spectroscopy (EIS). The weight loss result indicated a significant drop in metal corrosion upon the introduction of the leaves extract to the salt solution. The correlation coefficient (R2) values obtained from isotherm study showed that Langmuir model best fitted the inhibitor extract adsorption on the metal surface. The values of the Gibb’s free energy of adsorption (?Gads) were negative and ranges between -17 to -9 kJ/mol. This indicates that the adsorption process of the leaves extract is both spontaneous and physical. The weight-loss, PDP and EIS results all showed incremental change in efficiency of the inhibitor as its concentration is raised. This reveals that BF leaves extracts offered a shield to low carbon steel in the simulated sea water environment.
Bio-Inspired Shark Skin Riblets for Centrifugal Pump Impellers: CFD and Experimental Analysis
This study aimed to investigate a new bionic approach to analyze a centrifugal pump through numerical simulations and compare the results with experimental findings. A centrifugal pump consisting of six backward-curved blades; models of the impeller were designed using the riblet structure of shark skin. The flow inside the pump was studied using k-epsilon (k-?) turbulence models. The k-model gave results closest to the real experimental data. In most studies, only design parameters are considered during computational fluid dynamics (CFD) analyses without consideration of experimental results. Here, a new bio-inspired technique called bionics is applied to the impeller of a pump. The experiments were carried out using a computer-controlled testing setup. The pump's performance parameters were analyzed using both CFD simulations and experimental tests on the duty point as per the manufacturer’s catalog, having a revolution of 2,900 rpm. The bionic impeller achieves a best efficiency point (BEP) at a discharge rate of 12 m³/hr, with a head of 32.75 m and an efficiency of 39.21%. The CFD results closely matched the experimental results at the design flow rate and at all other tested flow rates. In addition, by integrating nature-inspired design with testing, this study contributes to the development of high-performance, sustainable pumps.
Editorial Information - Vol 22_Issue 5_December_2025