LAUTECH Journal of Engineering and Technology (LAUJET)
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Evaluation of the effect of doubling the stator slot number of a permanent magnet machine
Get PDFThe slot numbers of an electric machine play an important role in the machine’s output performance(s). Thus, the significance of doubling stator slot number of a Double Stator (DS) Permanent Magnet Machine (PMM) is presented in this study; to evaluate its impact on the overall electromechanical output of the considered machine and for better guide on appropriate slot-pole number combinations of the chosen machine type. The number of slots considered is six (6) slots and its corresponding binary is taken to be twelve (12). The machine indices comprise: flux linkage, induced voltage, torque, loss, power, and efficiency. Finite Element Analysis (FEA) is implemented in this investigation using MAXWELL-2D software. The study shows that the 12-slot machine configuration has higher flux linkage, induced voltage, power, and torque values compared to its equivalent 6-slot machine. The predicted shaft torque and power of the 6-slot machine are 0.93 Nm and 353.5 W, respectively, while the corresponding values obtained for 12 slots are 1.42 Nm and 491.3 W. However, greater electromagnetic loss and consequent lower efficiency are obtained from the 12-slot machine type, coupled with high usage of magnetic materials and likely higher cost consequences. The investigated machine is suitable for in-wheel traction applications
Characterization of bio-oil yield from catalytic pyrolysis of Zea mays indentata corncob
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In this study, the effect of zinc oxide catalyst on the quality of bio-oil from catalytic pyrolysis of Zea mays indentata corncob in a fixed bed reactor at optimum bio-oil yield condition was determined. Non-catalytic pyrolysis was carried out in the temperature range of 450 – 600 oC and residence time range of 20 – 35 mins, according to D-optimal design of Design Expert software (version 13.0.1), to determine the optimum condition for bio-oil yield. Catalytic pyrolysis was carried out at the optimum condition for bio-oil yield with biomass to catalyst (b/c) weight ratios in the range 97.5/2.5 - 90/10, according to mixture methodology formulation of Design Expert Software (version 13.0.1). Elemental composition and the basic fuel properties of the bio-oils at optimum bio-oil yields conditions, including viscosity, pH value, ash content and flash point, were determined and compared with those of non-catalytic pyrolysis bio-oil. The highest bio-oil yield (44.94 wt.%) from non-catalytic pyrolysis was obtained at the temperature of 550 ? and residence time of 25 minutes. The highest bio-oil yield (37.45 wt.%) from catalytic pyrolysis at the optimum temperature (550 ?) was obtained at biomass/catalyst ratio of 90/10. Catalytic pyrolysis bio-oils possessed higher carbon and hydrogen at b/c ratios of 96.67/3.33, 92.5/7.5 and 96.67/3.33. but lower oxygen and sulphur at 96.67/3.33, 92.5/7.5 and 90/10 than non-catalytic pyrolysis bio-oil. The use of catalyst reduced the viscosity, ash content (at b/c ratios of 96.67/3.33 and 97.5/2.5), and increased the pH value of bio-oils (at b/c ratios of 95/5 and 90/10). Catalytic pyrolysis improved the quality of pyrolysis bio-oil and can be moderately blended with petroleum diesel to power internal combustion engines
The Geochemical and mineralogical characterization of Tajimi iron ore in Kogi State and determination of its flotability nature
No full textThis research focuses on the geochemical and mineralogical characterization of Tajimi iron ore, located in Kogi State, Nigeria, with the aim of evaluating its industrial potential through froth flotation. A comprehensive analysis of the ore was conducted using techniques such as X-ray Fluorescence (XRF), X-ray Diffraction (XRD), Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM/EDS), and petrographic analysis, followed by a beneficiation via froth flotation method. The chemical composition of the crude ore was determined to be 62.166% Fe2O3 and 18.568% SiO2, with other trace elements also identified. Mineralogical analysis revealed the presence of goethite and cristobalite as the dominant minerals, with significant interlocking within the ore matrix, which facilitates the comminution process. Froth flotation was employed to enhance the iron concentration, resulting in a froth concentrate with 68.260% Fe2O3 and a depressed product with 68.006% Fe2O3. The recovery rate of iron oxide in the concentrate was 32.941%, with an enrichment ratio of 1.098 and a concentration ratio of 3.333, indicating a successful beneficiation process. The findings suggest that Tajimi iron ore has significant industrial potential, though further refinement is needed to reduce silica and other impurities
Development of a Fingerprint-Based Gender Detection System Using an Optimized Convolutional Neural Network
Get PDFBiometrics is a technology that identifies or verifies individuals based on unique physical or behavioral traits, offering a reliable form of authentication in sectors like healthcare, law enforcement, and security. Existing gender detection systems using fingerprints face challenges due to poor image quality and complex ridge patterns, while Convolutional Neural Networks (CNNs), though promising, are hindered by issues like overfitting, slow convergence, and getting trapped in local minima. Therefore, this study developed a fingerprint-based gender detection system through the optimization of CNN with Whale Optimization Algorithm. A dataset of 2,200 gender-labelled fingerprint images (1,320 male and 880 female) was acquired from Kaggle.com. The images underwent preprocessing involving cropping, grayscale conversion, histogram equalization for enhancement, and edge detection filtering to eliminate noise. Optimized CNN model was formulated using Whale Optimization Algorithm (WOA) by tuning CNN hyperparameters: number of neurons and dropout rate. The resulting WOA-CNN was employed for feature extraction (edges, texture patterns, shapes) and detection of fingerprint images. The model was implemented in MATLAB R2023a. Performance was evaluated using accuracy, sensitivity, specificity, false positive rate, precision, and recognition time, with an 80-20% training-testing split. CNN achieved 95.86% accuracy, 96.44% sensitivity, 95.00% specificity, 5.00% false positive rate, 96.66% precision, and 99.90 s recognition time. WOA-CNN achieved 97.23% accuracy, 97.58% sensitivity, 96.70% specificity, 3.30% false positive rate, 97.80% precision, and 87.40 s recognition time. This research showed WOA-CNN outperformed CNN in all metrics. It is recommended for use in biometric authentication, security checkpoints, and forensic investigations
Review of N-Bundled Conductors on Right-of-Way in Transmission Network Reinforcement in Electrical Systems
Get PDFTransmission line expansion has become one of the critical network planning strategies to ensure the continuous evacuation of power. Right-of-way (ROW) has posed significant challenges due to an increase in population and rural-urban development. This research therefore reviews various methodologies of investigating the effect of N-bundled conductors on right-of-way and power system parameters such as voltage, current, power and load. The review of technical literature reveals that the effects of transmission lines bundling of conductors on the right-of-way were not considered in most cases of the literature reviewed. The changes in the electrical power system parameters with changes in conductor area and bundling of conductors were not examined in most cases of the papers reviewed. Even the relationship between transmission line expansion and bundling of conductors was not studied in most cases. To that effect, this study therefore proposed solutions to the above-mentioned shortcomings observed in the area of transmission network expansion
Health Risk Assessment of Nitrate Concentration in Soil and Water within the Sango area, Ibadan
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Drinking water contamination by nitrates poses serious health risks, particularly to infants and pregnant women. Rapid urbanization in Sango, alongside poor sewage and industrial waste management, intensifies nitrate pollution, endangering public health. The aim of this research is to assess the nitrate concentration in drinking water sources in Sango area of Ibadan metropolis. Twenty-two sampling points (SW1–SW22) were selected using stratified sampling. Water samples were collected during both rainy and dry seasons. Nitrate concentrations and key physicochemical parameters pH, temperature, turbidity, dissolved oxygen (DO), and electrical conductivity (EC) were measured. Daily nitrate intake was estimated across age groups and compared with WHO guidelines. Nitrate levels ranged from 125 - 285 mg/L (rainy season) and 67.42 - 153.67 mg/L (dry season), significantly above WHO limits. pH ranged from 6.1 - 9.3 and 6.32 - 9.47; turbidity, 28.6 - 49.3 NTU and 20.34 - 34.54 NTU; DO, 5.02 - 8.9 mg/L and 4.54 - 7.63 mg/L; EC, 206.4 - 907.5 µS/cm and 230.72 - 980.44 µS/cm during rainy and dry seasons, respectively. Estimated nitrate intake across all adult age groups exceeded the WHO acceptable daily intake thresholds, indicating significant health risks. The total nitrate intake across body weight categories exceeded WHO's estimated acceptable nitrate intake (mg/kg) in both rainy and dry seasons. Elevated levels, especially during the rainy season, pose significant health risks, surpassing WHO limits across demographics and seasons. Enhancing water treatment infrastructure, promoting rainwater harvesting, and improving filtration systems during periods of peak contamination can significantly reduce nitrate exposure
Inverter-based resources and grid stability: a comparative study of grid-forming and grid-following control: Inverter-based resources and grid stability: a comparative study of grid-forming and grid-following control
No full textThe increasing penetration of renewable energy sources has accelerated the transition from synchronous generator–dominated power systems to grids heavily supported by Inverter-Based Resources (IBRs). Within this transformation, two distinct inverter control paradigms have emerged: Grid-Following Inverters (GFLs) and Grid-Forming Inverters (GFMs). GFLs synchronize to the existing grid voltage and supply controlled active and reactive power, while GFMs establish their own voltage and frequency references, thereby providing system-strengthening services traditionally delivered by synchronous machines. This paper presents an in-depth comparative analysis of GFL and GFM technologies, focusing on their control principles, dynamic performance, stability characteristics, and roles in renewable energy integration. A critical evaluation of their applications, limitations, and hybrid deployment strategies is also provided. The analysis highlights that GFMs are increasingly necessary to enable stable, resilient, and renewable-dominated future grids
Optimization of coagulation-flocculation process for wastewater treatment using selected coagulants: Optimization of coagulation-flocculation process for wastewater treatment using selected coagulants
No full textPlant-based coagulants represent a new paradigm in wastewater treatment, advancing the transition to a green economy and promoting cleaner production. This research focuses on the coagulation-flocculation process for the treatment of wastewater using indigenous and imported alum combined with the bark of the Brideliaferrugineae (BF) tree as a natural coagulant. Two hundred grams (200 g) of B.F (Iran-Odan) bark was soaked in 2-litres of distilled water for three days, 1:10. The qualitative and quantitative phytochemical parameters of the bark extracts - Alkanoid, Sapon, Tannin, Phloba tannin, Anthraquinone, flavonoid, steroid and Terpenoid, were determined in percentage using Thin-layer chromatography (TLC), High-performance liquid chromatography (HPLC) and UV-Vis spectrophotometry approach. The optimal ratio of BF respectively mixed with imported and indigenous alums. The physicochemical properties of normal and treated wastewater which include pH, EC, Turbidity, Phosphate, Chemical Oxygen Demand (COD), and Biochemical Oxygen Demand (BOD), were also determined. The effectiveness of each dosage of Alum and BF was determined through laboratory analysis. The optimal mixture that produced desirable results as compared with the effluent standard of the Food and Agriculture Organisation (FAO) was determined. The effectiveness of each dosage of Indigeneous Alum - BF mix ranged from 16.56-24.56%. The corresponding value for the Imported Alum - BF mix ranged from 16.41-26.11%. The optimal mix ratio of the coagulation-flocculation process was 50:50 of Alum and BF mix. Both mix effectively treated industrial and domestic wastewater and should be given more attention
Development of an enhanced support vector machine face recognition system
Get PDFFace recognition biometric authentication focuses on uniquely recognizing human facial appearance based on inherent physical traits of the face for application in access control. The use of face for recognition has been proven to be highly reliable and effective. This research performed a performance evaluation of SVM-based variants in the recognition of facial images. Six facial expression images, each from sixty individuals, were locally acquired using a Canon EOS 2000D digital camera at 200×200-pixel resolution, 240 images were used for training, while 120 images were used for testing. The acquired images were converted into grayscale and normalized using the histogram equalization method. Features classification was carried out using a Support Vector Machine for PCA-PSO and PCA, respectively. The performance of the two techniques was evaluated and compared at a 0.42 threshold using Recognition Accuracy (RA), Precision (P), Sensitivity (S), and Recognition Time (RT). The validation of the techniques was done using t - a t-test at a significant 5% level. The RA, P, S, and RT were 97.50%, 97.80%, 98.89%, 1487.16 s, and 3.80s for PCA-PSO-SVM, while the corresponding values for PCA-SVM were 95.83%, 96.70%, 97.78%, 1861.79 s, and 22.96 s, respectively. The paired t-test was P = 0.001 with a mean difference of 2.5%. The PCA-PSO-SVM technique performed better than PCA–SVM for all metrics. A face recognition system based on PCA-PSO-SVM is a more reliable security surveillance system than PCA-SV
Investigation of process parameters for producing bio-oil from luffa cylindrical fiber in a fixed bed reactor using pyrolysis process
Get PDFThis study was performed to assess the impact of pyrolysis parameters on the yield of pyrolytic bio-oil during the thermal degradation of luffa cylindrical fiber in a fixed-bed reactor. The study revealed that the optimal bio-oil output of 29 wt% was attained at a reactor temperature of 600 °C, a biomass particle size of 4 mm, and a nitrogen gas flow rate of 1.5 L/min. The Gas Chromatography-Mass Spectrometry (GC-MS) analysis of the bio-oil revealed the presence of phenols, alcohols, carboxylic acids, ketones, alkenes, alkanes, aldehydes, and aromatics, indicating that the pyrolysis of luffa cylindrical fiber could be a viable approach for producing renewable fuels and chemicals while mitigating environmental pollution concerns