LAUTECH Journal of Engineering and Technology <p>LAUTECH Journal of Engineering and Technology (LAUJET) is a leading internationally referred journal in the fields of science, engineering and technology. It is a journal founded by academics and educationists with substantive experience in industry. The journal is an online open-access journal with a yearly print version of its volumes/issues made available to interested persons/institutions. The basic aim of the journal is to promote innovative ideas in fields relating to the sciences, engineering and technology. The basic notion of having a wide area of focus is to encourage multidisciplinary research efforts and seamless integration of diverse ideas that might be gleaned from the papers published in the journal.</p> <p>&nbsp;</p> Faculty of Engineering and Technology, Ladoke Akintola University of Technology, Ogbomoso, Nigeria en-US LAUTECH Journal of Engineering and Technology 1597-0000 Determination of wear resistance, frictional power loss, and thermal conductivity of aluminium metal composites <p><em>This study addresses the need for lightweight, wear-resistant aluminium alloys in the automotive industry to combat climate change. Here, aluminum composites reinforced with various combinations of silicon carbide (SiC) and aluminum oxide (Al<sub>2</sub>O<sub>3</sub>) were fabricated from recycled aluminum cans using stir-casting. Wear resistance, thermal conductivity, and frictional power loss were evaluated. The serial tests of frictional power loss, thermal conductivity, and wear resistance results on PA, CS, 4% SiC-2%AO, 4% SiC-4%AO, 4% SiC-6%AO, 4% SiC-10%AO, and 6% RHA/4% PSA samples are the following: 1000, 1000, 850, 750, 550, 450, and 550 watts; 270, 260, 220, 200, 180, 125, 185, and W/m-K; and 0.24, 0.18, 0.3, 0.23, 0.12, 0.06, and 0.24 mg, respectively. The 4%SiC/10%Al2O3 composite demonstrated superior wear resistance against plastic deformation, minimal frictional power loss, and the highest thermal conductivity among the tested samples. This improvement is attributed to a wear-reacted layer formed during testing. Interestingly, the 4%RHA/6%PSA composite, utilizing alternative reinforcements, offered comparable thermal conductivity to other SiC/Al2O3 combinations, suggesting potential for further exploration. This research promotes the use of recycled materials while achieving the desired properties for sustainable automotive applications</em></p> B. J. Olorunfemi I. A. Olumoroti O. T. Oginni I. A. Olumoroti ##submission.copyrightStatement## 2024-06-06 2024-06-06 1 10 Investigating impacts of ammonium phosphate on ash yield from co-combustion of sugarcane bagasse and banana leaves <p><strong><em>This study aimed to investigate the influence of mono ammonium phosphate (MAP) on ash yield from the co-combustion of sugarcane bagasse and banana leaves in a muffle furnace. An I-Optimal design of the Combined Methodology, embedded in Design Expert (version 13.0.5), was employed to optimize ash yield, considering various particle sizes, additive concentrations, and temperatures. The mixed samples were ashed in a muffle furnace to a constant weight, and the ash yield was analyzed using statistical tools to assess the model's quality. The MAP additive was most effective at concentrations between 4% and 7%, beyond which ash yields increased significantly. The optimal composition was determined to be 75% sugarcane bagasse, 20% banana leaves, and 5% ammonium phosphate at 950°C, resulting in the lowest ash yield of 6.46%. The presence of MAP in the biomass mixture significantly reduced ash yield. The model's R² and adjusted R² values were 0.9825 and 0.9099, respectively, indicating accurate determination of the model coefficients. This study demonstrates that ammonium phosphate additive has great potential in mitigating ash-related problems in biomass combustion.</em></strong></p> K. O. Oladosu A. S. Olawore E. A. Ponle I. A. Adeniran J. O. Oderinde ##submission.copyrightStatement## 2024-06-06 2024-06-06 11 24 IOT in Smart Villages: Challenges and  Prospects <p><strong>Smart villages, which use the Internet of Things (IoT), offer a viable solution to the issues that rural communities confront around the world. This study provides a complete overview of the role of IoT technology in transforming rural communities into long-term, technologically advanced centers. It investigates the fundamental elements of smart villages, such as renewable energy, digital connection, agriculture, healthcare, and community interaction. It also addresses the benefits, constraints, and future prospects of using IoT in smart village programs. This research will analyze existing literature and case studies to provide insights into the potential benefits and best practices for using IoT solutions in rural development.</strong></p> M. R. Akinsiku B. Ubochi ##submission.copyrightStatement## 2024-06-06 2024-06-06 25 39 Effects of magnetic field on removal of light non aqueous phase liquid from unsaturated zone using steam injection <p><strong>Abstract</strong></p> <p><strong>&nbsp;</strong>Unsaturated zone is of great importance in providing water and nutrients that are vital to the biosphere and often the main factor controlling water movement from the land surface to the aquifer. Steam injection for remediation of porous media contaminated by NAPLs has been shown to be a potentially efficient technology. However, the need for its improvement in recovery efficiency using other methods has been a subject of continuous study. The aim of this study was to carry out the experiments to investigate the effect of magnetic field on the removal of NAPLs from unsaturated zone using Steam Injection An unsaturated zone of a sand box of interior dimensions 110 x 74 x 8.5 cm was polluted at different period with 200 mL&nbsp; of Toluene. Steam injection experiment with flow rate of &nbsp;0.01 m<sup>3</sup>/s was performed to determine the recovery efficiencies of Toluene only in an unsaturated zone containing sand of porosity 0.42 and permeability of 0.001163779 cm/s with the introduction of varying magnetic field 1-3T in step of 1T. The results for the recovery efficiency of Toluene using steam injection only was 80.30% while that of steam injection and magnetic field at 1-3 T yielded 83.70-86.60 %. The results of recovery efficiency of steam injection with magnetic field were 4.23-7.85 % higher than the result of steam injection only for LNAPL (Toluene). A combined application of steam injection with magnetic field appreciably enhances the removal of Non Aqueous phase liquids from Unsaturated Zone.</p> <p>&nbsp;</p> <p>&nbsp;</p> A. A. Adegbola A. I. Abioye Y. O. Yakub ##submission.copyrightStatement## 2024-06-08 2024-06-08 40 51 Gas turbine bearing vibration monitoring using potable vibrometer <p><em>This paper focuses on the use of potable vibrometer to undertake gas turbine condition monitoring and fault detection of an industrial gas turbine power plant in Ajaokuta, Nigeria. Validation of the potable vibro-meter readings is done by comparing results obtained using the potable vibrometer with results gotten from the plant vibrometer transducers. After comparing bearing vibration amplitude results at the gas turbine exciter and generator ends, results for the test case looked at indicate that very good correlation exist between the two readings (above 90%). Conclusion reached is that measurement accuracy of the potable vibrometer reading is highly dependent on the visibility of the component measured and their corresponding vibration measurement sensors (Accelerometers and velocity meters).</em></p> <p><em>&nbsp;</em></p> <p><em>Key words: Ajaokuta, Potable Vibrometer, Fluke, Geregu power.</em></p> A. K. Mohammed I. I. Ozigis M. N. Lawal ##submission.copyrightStatement## 2024-06-08 2024-06-08 52 64 Optimization of the effects of process parameters on nutritional and microbial qualities of canned snail meat using Taguchi method <p>Snail farming being a low cost farming process that requires minimal professional skill requirements has gained more attention in recent times. Snail meats are rich in protein but are vulnerable to microbial contamination due to their habitat. Smoking and drying are the most common method of preserving snail meat in Africa, especially Nigeria. The quest to retain the nutritional value of snail meat while preserving it fresh has necessitated further investigation. Fresh snail meats were preserved by canning in three packaging media (brine, vinegar, brine-vinegar). The effects of canning time, temperature, nitrite concentration and packaging media on protein content, fat content, moisture content, ash and pH were investigated using Taguchi model. Statistical analysis was carried out. Process parameters were also optimized and validated for effective snail meat canning. Temperature was discovered to be the most controlling parameter for the variation in protein, fat and moisture content. Carbohydrate and ash content were not significantly affected by the process parameters. The optimum canning process parameters, 50 mins, 121℃, brine and 100 ppm sodium nitrite concentration gave 18.98% ±0.11 protein content, 1.51% ±0.09 ash content, 1.40% ±0.04 fat content, 1.88% ±0.13 carbohydrate content, 76.23% ±0.08 moisture content and pH of 5.93 ±0.06. The absence of heterotrophic bacteria, fungi, coliform and <em>Staphylococci </em>in the validation experiment confirmed the efficiency of the optimum conditions and its suitability in the commercial preservation of canned fresh snail meat.</p> L. A. Oyesola L. A. Adejumo M. O. Jimoh B. O. Solomon ##submission.copyrightStatement## 2024-06-08 2024-06-08 65 79 The Corrosion inhibitory performance of hybridized rice-husk extract and biopolymer waste on food-compatible mild steel in acidic media <p>Metal corrosion is frequently the outcome of the reactive interaction between food's corrosive components and metal alloy during processing and packaging. This study used gravimetric and depth of attack methodologies to examine performance of hybridized rice husk extract and chitosan, as a corrosion inhibitor for mild steel in 1 M HCl. Rice husk was subjected to phytochemical screening in order to choose the best material combination. Gas chromatography–mass spectrometry was then used to characterize the extract. Fourier transform infrared spectroscopy was used to characterize the corrosion film solution and chitosan synthesized from residual biopolymer fish scale. The rate at which the coupon corroded with and without rice husk extract and chitosan was assessed in relation to temperature, concentration, and time. The formation of a film over the metal surface was facilitated by the presence of polycyclic chemicals, tannins, and cellulose, thus aiding corrosion. Inhibition efficiency increased with increase in temperature and concentration of rice husk extract. Kinetic parameters showed that Langmuir isotherm is the best fit because the R<sup>2 </sup>value is close to unity. The addition of 5:1 ratio of rice husk to chitosan shows a great difference as the inhibition efficiency increase with increasing temperature to 80% inhibition efficiency</p> B. K. Adeoye ##submission.copyrightStatement## 2024-06-08 2024-06-08 80 92 Electromechanical analysis of a machine <p>Output performances such as induced-voltage and torque of an electric machine are investigated in this study, with particular reference to its pole number effects. The analyses are made using 2D-finite element method. The study revealed that the investigated machine having 6 stator slots and 11 pole number i.e. 6S/11P has the highest amount of magnetic remanence, coercive force and flux linkage amongst the compared machine types. Consequently, these highest values would yield the largest output torque in the machine. Desirably, high output torque is also relatively realized in the 6S/13P machine type. Nevertheless, both the 6S/11P and 6S/13P machine types would be adversely affected by large effect of magnetic force on its rotor. The greatest field-weakening ability, determined as a measure of the machine’s speed ratio is provided by 6S/13P machine topology and this trait is desired in traction and propulsion systems. The most competitive torque is also obtained from 6S/13P machine, considering its yield with respect to the employed magnet volume.</p> C. C. Awah O. Obasi C. A. Amaghionyeodiwe G. C. Diyoke I. K. Nnabuenyi S. E. Oti ##submission.copyrightStatement## 2024-06-08 2024-06-08 93 100 Synthesis and characterisation of CaO nanoparticle from oyster shell using sol-gel method <p>Because human activity is constantly increasing the content of heavy metals, heavy metal removal becomes a major challenge in wastewater treatment. In an attempt to provide an innovative and sustainable option for addressing the said challenge, this study is aimed at the synthesis and characterization of nano-based CaO biosorbent from oyster shell. The sol- gel method was used to synthesize the biosorbent, characterized using FTIR, XRD, SEM and BET respectively.&nbsp; From the analysis conducted, the developed CaO nanoadsorbent has a point of zero charge of 5.6, indicating stable charge balance. The biosorbent was chemically characterized by the presence of a number of functional groups, most notably the –OH and C-H. The CaO nanoadsorbent was found to be crystalline in nature as revealed by XRD analysis. Findings from the BET indicated the material has a surface area of 344.528 m<sup>2</sup>/g, specific pore volume of 0.170cc/g and pore diameter of 2.118nm, indicating that it is mesoporous structurally. The results of the characterization reveal that the CaO nanoadsorbent present a suitable option for treatment of wastewater based on its associated attributes.</p> K. N. Akatobi ##submission.copyrightStatement## 2024-06-12 2024-06-12 101 109 Software development for design of solar energy photovoltaic system for rural and urban communities in nigeria <p>Solar Photovoltaic systems for a given load work dependably and remain the finest alternative regarding numerous utilizations only when preceded with accurate pre-installation design. The output power generated and ability of such Photovoltaic system to meet load demand by a solar photovoltaic (PV) system greatly depends on accurate sizing of the PV system’s parts. The Solar planner software developed in this study provides an effective solution to problems associated with most pre-installation design of Photovoltaic systems in Nigeria. The software accurately carries out the sizing of the various system components, thereby providing the technical personnel with sufficient information about the PV project design prior to installation stage. It also uses the average daily sunshine method and design equations modeled for PV systems to achieve the correct sizing of the components. It follows a procedural sequence in executing the sizing equations developed in JAVA programming language on a JAVA developmental Kit (JDK 1.6). The software produced useful parameters for the technical personnel. The parameters include the total power, design energy, capacity of the solar panel required, number of solar panel required, capacity and number of batteries required, size of charge controller and inverter rating, optimum tilt angle and cable size. The use of this solar planner software for design of PV system gives an effective, faster, cost effective and a reliable accurate sizing and PV system’s improved performance in the Nigerian solar business market.</p> O. A. Akinola A. S. Afolabi A. F. Agbetuyi I. Balogun I. Adebayo J. L. Adedokun ##submission.copyrightStatement## 2024-06-20 2024-06-20 110 121 Implementation of a sustainable real-time air quality monitoring system using the Internet of Things for Kaduna metropolis, Nigeria <p>The environment is sustainable if it is free of air, water, and soil pollution. This agrees with the United Nations Sustainable Development Goal Three (SDG3). However, urbanization and industrialization have aggravated the rise of air pollution which are hazardous to both human health and society. Ingestion of large quantities of air pollution gases is one of the greatest health risks in the environment which often leads to death, brain damage, and loss of consciousness at high doses. Some common sources of carbon monoxide (CO), the most severe of these gases, can be traced to the incomplete combustion of cars’ fuel, malfunctioning equipment, clogged chimneys and vents, and interior use of portable generators. Traditional ways of monitoring pollution are laborious and involve inefficient processes. To address this challenge, this paper implemented a real-time Air Quality Monitoring System using the Internet of Things (IoT) to measure the concentration of CO. The IoT devices were used to collate data within specific areas. The data collected, by the sensor, were processed using software which is then trained in the system to predict air pollution levels based on historical data. The system also includes a user interface that allows users to view real-time air pollution data and receive alerts when pollution levels exceed the safe threshold. The system was tested in different environments, Air Force Institute of Technology and Kawo; densely populated areas of Kaduna State, Nigeria. This was done to demonstrate the high level of accuracy and reliability of the system. The correct implementation of the developed system has the potential to be used as a tool for researchers, and for the general public to better understand and address the problem of air pollution.</p> O. O. Tooki ##submission.copyrightStatement## 2024-06-20 2024-06-20 122 127 Iron oxide Green synthesized nanoparticles for improved performance in Monolithic Dye Sensitized Solar Cells <p>In order to improve photovoltaic efficiency in Monolithic Dye-Sensitized Solar Cells (MDSSCs), this study examined the effects of incorporating green produced iron oxide nanoparticles to a nanoporous carbon counter electrode. An extract from the leaves of <em>Ocimum gratissimum</em> was effectively used to synthesize iron oxide nanoparticles. The development of iron oxide nanoparticles was verified by optical absorption in the 350–450 nm range. With an average crystallite size of 47.9 nm, XRD patterns demonstrated the crystalline nature of the Iron oxide nanoparticles. Chemical bonds that may responsible for the nanoparticle production were found using FTIR investigations. An impressive 135.3% boost in efficiency was recorded for cell containing the Iron oxide nanoparticles, according to the MDSSC performance evaluation where DSSC without nanoparticles had a lower solar-to-electric power conversion efficiency of 1.7%, an open circuit voltage of 0.2625 V, a short-circuit current of 0.0723 mA/cm<sup>2</sup>, and a fill factor of 0.3630. The FeO CEs cell had an open-circuit voltage of 0.4274 V, a short-circuit current of 0.1042 mA/cm<sup>2</sup>, and a fill factor of 0.46. Their solar-to-electric power conversion efficiency was 4.0%. The potential of incorporating green-synthesised iron oxide nanoparticles into MDSSC counter electrode was shown by their great biocompatibility and even dispersion.</p> A. J. Abiodun G. A. Alamu O. Adedokun O. O. Daramola Y. K. Sanusi ##submission.copyrightStatement## 2024-06-27 2024-06-27 128 137 Construction of ternary diagram for liquid-liquid extraction process using computer-based program <p>The&nbsp;Liquid-Liquid Extraction (LLE) is a liquid-liquid phase mass transfer process in which solute chemicals are transferred between two immiscible or partially miscible liquids due to difference in solubility of the solutes in the two liquids. The phase equilibrium relationships are generally inconvenient to handle algebraically, therefore, LLE computational analyses are usually made graphically. Manual construction of ternary diagram becomes cumbersome, tedious and time consuming when used for a process that requires large number of stages. Therefore, the aim of this work was to develop a customized computer package for the ternary diagram. The customized computer package for the ternary diagram construction was achieved with the use of fuzzy inference system toolbox and primitive line function in MATLAB. The computer program was test-run using data from literature to determine theoretical number of stages for a given LLE separation process. The result compared well with the existing literature result.&nbsp;</p> A. A. Sulayman D. O. Araromi O. S. Ayodeji K. K. Salam ##submission.copyrightStatement## 2024-06-27 2024-06-27 138 147 Development of an intrusion detection system using mayfly feature selection and artificial neural network algorithms <h3><strong>Protecting the privacy and confidentiality of information and devices in computer networks requires reliable methods of intrusion detection. However, effective intrusion detection is made more difficult by the enormous dimensions of data available in computer networks. To boost intrusion detection classification performance in computer networks, this study developed a feature selection mode for the classification task. The proposed model utilized the Mayfly feature selection algorithm and ANN as the classifiers. The model was also tested without a mayfly algorithm. The model's efficacy was determined through a comparison of its accuracy, specificity, precision, sensitivity, and F1 score. The experimental outcomes revealed that the proposed model is more efficient than existing models based on the performance evaluation and the CIC-IDS 2017 dataset employed in this research. Accuracy scores of 99.94% (using Data+mayfly+ANN) and 90.17% (using Data+ANN) were attained after experimentation. In comparison to existing models, the proposed model yielded better results in terms of accuracy, sensitivity, specificity, and F1-score metrics. The model's sturdiness can be attributed to the use of mayfly techniques, which harness the strength in PSO, GA and FA for selecting optimal feature subsets. The results of this research provide a reliable dimensionality reduction model that may be used in the field of computer networks for intrusion detection and enhancement of security in computer networking environments.</strong></h3> M. F. Edafeajiroke ##submission.copyrightStatement## 2024-06-28 2024-06-28 148 160 Three phase microcontroller based automatic change-over selection switch <p><em>The significance of electricity in a developed country cannot be underestimated because power instability problem affects the economy growth, productivity and infrastructure development. The issues of phase failure, losses and phase imbalance earth fault are main causes that lead to unstable and erratic power supply. Most homes and office complexes where single-phase supply is needed are supplied with three phases of power supply to allow change from one phase to another when there is fluctuation or complete outage of power supply on a particular phase. This operation is normally done manually and has caused a setback in terms of time wastage, strenuous operation, susceptibility to fire outbreak, electric shock and high maintenance frequency. When voltage supply on a phase is below 220V or above 415V, this system automatically disconnects the load from the phase and connects to another where the required condition is met. Therefore, this paper presents a Microcontroller Based Automatic Transfer Switching System which is made up of voltage sensing circuit, Hall Effect current sensor, relays, LEDs and LCD of PIC16F877A microcontroller. A system flow chart was developed, programmed with MikroC software and simulated using Proteus electrical software design. A 10KVA single phase generator was used as alternate power source. The load capacity of the design was determined by decoupling Maxwell<sup>’</sup>s Equations of 8KW and power loss using pointing vector equation as 0.25% of the peak load. The switch is tested to have function optimally within ±5% nominal voltage of 220 - 415V supply and produced approximately 20 seconds elapses during the entire process of power supply changeover.&nbsp;&nbsp;</em><em>Hence this device is suitable for Industrial and Domestic use where 3-phase power supply is available with a stand-by power source.</em></p> O. A. Akinola A. S. Afolabi A. T. Adebayo E. K. Ojo A. A, Raji ##submission.copyrightStatement## 2024-06-28 2024-06-28 161 174 Winding inductance predictions of a machine <p class="LRECAbstractHeading" style="margin: 0cm; margin-bottom: .0001pt; text-align: justify; text-justify: inter-ideograph; line-height: normal;"><span lang="EN-CA" style="font-size: 12.0pt;">The winding inductances of a double stator machine are analyzed in this study. Finite element analysis is deployed using MAXWELL-ANSYS software. It is revealed that the machines that have even number of poles i.e. 10-pole and 14-pole, exhibited larger amount of both self and mutual inductance values. The 10-pole and 14-pole machine types have relatively larger direct-axis inductance compared to that of its 11-pole and 13-pole counterparts; nevertheless, with <span style="color: black;">comparably </span>lower quadrature-axis inductances. The machine types that have odd number of poles seem to possess lesser sensitivity to its inductance-current relation, unlike its equivalent even number of pole categories. Predicted peak magnetic axis force value on the rotor of 10-pole, 11-pole, 13-pole and 14-pole machine varieties at 30 W is: 0.18 N, 87.60 N, 10.95 N and 0.13 N, respectively.</span></p> C. C. Awah C. A. Amaghionyeodiwe G. C. Diyoke O. Obasi I. K. Nnabuenyi S. E. Oti ##submission.copyrightStatement## 2024-06-28 2024-06-28 175 181 Optimized convolution neural network-based model for detection and classification of pulmonary diseases. <p><em>Pelican Optimization Algorithm-based Convolutional Neural Network (POA-CNN) method for the automated identification of pulmonary disorders such as COVID-19 and pneumonia is proposed in this research. The method makes use of several processing layers in order to comprehend the representation of stratified data. The three primary phases of the model are feature extraction via POA-based hyperparameter optimization, image classification, and image pre-processing.&nbsp; This approach improves existing systems' performance in detecting pulmonary diseases, highlighting the potential of deep learning in identifying and categorizing human diseases. The study uses a resizing, grayscale, and augmentation method to optimize an existing CNN model. A Convolutional Neural Network (CNN) is then applied to classify Pneumonia and Covid-19 cases. The proposed model achieves an accuracy rate of 97.28 and 97.00%, outperforming existing models. This technique is effective in detecting and classifying other pulmonary diseases, and can be used to automatically detect and classify these diseases. Higher accuracy findings show how successful the model is, making it a useful tool for pulmonary illness identification.</em></p> T. A. Olajide ##submission.copyrightStatement## 2024-06-28 2024-06-28 182 192