Journal of Advances in Science and Engineering
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Comparative studies of surfactant-enhanced-water, WAG and surfactant-enhanced-WAG injections in concurrent development of thin oil rim reservoir
Get PDFThe goal of this paper is the comparative analysis of three injection fluid options: Surfactant-enhanced-Water (SeW), Water Alternating Gas (WAG) and Surfactant-enhanced-WAG (SeWAG). The objectives are to identify the best option with the highest oil and gas displacement efficiency and the best development strategy for optimum recoveries in concurrent development of an oil rim reservoir. The Eclipse simulator was used because of its robust ability in simulating various injection options of an oil rim reservoir in a green field. Four scenarios (base case/no injection, SeW, WAG and SeWAG injections) were simulated under the same conditions to determine injection option with the best displacement efficiency and recoveries of oil and gas. Statistical analysis using Pareto chart was performed for proper identification of the option with the best recoveries. The result showed that SeWAG injection ratio 1:4:2 and injection cycles 56 gave the best recoveries for oil and gas with displacement efficiency of 0.08 and 0.332 respectively, followed by SeW injection with values of 0.073 and 0.331 respectively, while WAG has the least performance. On the Pareto chart, SeWAG simulation result has the highest percentage among the options with the best recoveries of 3.35 MMSTB oil and 16.05 BSCF gas, which is 12.53% and 16.12% of oil and gas in place after 9.6% of oil and 15.1% of gas have been recovered by natural depletion. Hence, this study has shown that two stages of development strategy (combination of natural depletion and SeWAG injection when the reservoir pressure is depleted) give cumulative effect for optimal recoveries in concurrent development of oil rim reservoir
The design and practical implementation of a six-phase induction motor
Get PDFThis thesis presents a re-designed conventional three phase 5-hp squirrel cage, 4-pole, 48 slots induction motor to a six-phase induction motor (SPIM). It also presents the in-depth of a single layer winding of a three-phase motor that was re-design to the six-phase split winding layout which was practically explained to the understanding of both the engineers and the technicians who normally find it difficult with windings of electrical machines. The optimized re-designed SPIM is presented in the MATLAB/Simulink environment to perform a comparative assessment of the different phase loss scenarios of the six-phase configuration with respect to the six-phase healthy case and its conventional three-phase induction motor. The result shows a comparative benefit of the six-phase induction motor over the three-phase induction motor; in such that in the near future because of its effective way to provide a higher reliability and sustainability under the loss of phase/phases condition it will be practically applied in the power driven devices/machines like in the area of Electric Vehicles, etc
A survey on artificial intelligence based techniques for diagnosis of hepatitis variants
Get PDFHepatitis is a dreaded disease that has taken the lives of so many people over the recent past years. The research survey shows that hepatitis viral disease has five major variants referred to as Hepatitis A, B, C, D, and E. Scholars over the years have tried to find an alternative diagnostic means for hepatitis disease using artificial intelligence (AI) techniques in order to save lives. This study extensively reviewed 37 papers on AI based techniques for diagnosing core hepatitis viral disease. Results showed that Hepatitis B (30%) and C (3%) were the only types of hepatitis the AI-based techniques were used to diagnose and properly classified out of the five major types, while (67%) of the paper reviewed diagnosed hepatitis disease based on the different AI based approach but were not classified into any of the five major types. Results from the study also revealed that 18 out of the 37 papers reviewed used hybrid approach, while the remaining 19 used single AI based approach. This shows no significance in terms of technique usage in modeling intelligence into application. This study reveals furthermore a serious gap in knowledge in terms of single hepatitis type prediction or diagnosis in all the papers considered, and recommends that the future road map should be in the aspect of integrating the major hepatitis variants into a single predictive model using effective intelligent machine learning techniques in order to reduce cost of diagnosis and quick treatment of patients
Application of nonlinear autoregressive neural network to estimation of global solar radiation over Nigeria
Get PDFIn this paper, surface data meteorological were used as input variables to create, train and validate the network in which global solar radiation serves as a target. These surface data were obtained from the archives of the European centre for Medium-Range weather forecast for a span of 36 years (1980-2015) over Nigeria. The research aims to evaluate the predictive ability of the nonlinear autoregressive neural network with exogenous input (NARX) model compared with the multivariate linear regression (MLR) model using the statistical metrics. Model selection analysis using the index of agreement (dr) metric showed that the MLR and NARX models have values of 0.710 and 0.853 in the Sahel, 0.748 and 0.849 in the Guinea Savannah, 0.664 and 0.791 in the Derived Savannah, 0.634 and 0.824 in the Coastal regions, and 0.771 and 0.806 in entire Nigeria respectively. Meanwhile, error analyses of the models using root mean square errors (RMSE) showed the values of 1.720 W/m2 and 1.417 in the Sahel region, 2.329 W/m2 and 1.985 W/m2 in the Guinea Savannah region, 2.459 W/m2 and 2.272 W/m2 in the Derived Savannah region, 2.397 W/m2 and 2.261 W/m2 in the Coastal region and 1.691 W/m2 and 1.600 W/m2 in entire Nigeria for MLR and NARX models respectively. These showed that the NARX model has higher dr values and lower RMSE values over all the climatic regions and entire Nigeria than the MLR model. Finally, it can be inferred from these metrics that the NARX model gives a better prediction of global solar radiation than the traditional common MLR models in all the zones in Nigeria
Heavy metals pollution potentials in the National Iron Ore Mining Company, Itakpe
Get PDFHeavy metals pollution potential in National Iron Ore Mining Company, Itakpe was investigated. Two mining sites located at the east mining pits such as M3O, which is 370 m above sea level and M2O, which is 350 m above sea level were studied. Sequential extraction techniques was utilised to examine the distribution effect of the heavy metals pollution potential on the environment. Twelve representative (six-soil, two-sediment, two-plant and two-water) samples were collected, pre-treated and prepared for this study. The atomic absorption spectrometer was used to analyse the concentration of the metals after the sequential and single-stage extractions were determined. Results showed that Chromium, Arsenic, Cadmium and Copper are more bioavailable in the study area than Lead and Iron. This findings indicate that human, animals and plants are exposed to toxic elements (metals and metalloids)
Effect of under belting a multiple V-belt drive
Get PDFThe paper seeks to explore the effect of under belting a multiple V-belt drive on the life of a given sets of belts. Under belting a device means using fewer belts than recommended by good design practices. The experiment investigates the incremental reduction of the number of belts by one and the attendant effect on the life of the whole belts set. The experiment is based on ten belts being the normal required to drive the load. The experiment emphasizes the effect of reducing one V belt on the life of the whole set. The experiment was based on 100% efficiency on the whole life of the whole sets from 10 belts, which is the required to drive the load. Effect of belt creep was neglected. It was progressively decreased by one and the whole belt life was evaluated based on the reductio
Experimental study on silver nanoparticles: synthesis, photo-degradation and analysis
Get PDFThe aim of present study was waste water treatment via advanced oxidation process (AOP). Wet chemical precipitation method was used to prepare silver nanoparticles (Ag NPs). The Ag NPs were employed for photo catalytic degradation of Congo red (CR) dye in aqueous medium. The scanning electron microscopy (SEM) investigation shows agglomerated form of Ag NPs. The average sizes of agglomerations are below 600 nm. Energy dispersive X-rays spectroscopy (EDX) and ultraviolet light visible spectroscopy (UV/Vis) also established the formation of Ag NPs. The photo-degradation study reveals that Ag NPs degraded by 73% of CR dye in 480 min. Catalytic dosage study shows the dye degradation was increased vice versa as increased the amount of Ag NPs and then almost level off after 0.025 g of catalyst. In pH study it was observed that degradation of CR dye increased as pH increased. The recovered catalyst study also significantly degraded the CR dye
Comparative study and experimental analysis of pellets from biomass sawdust and rice husk
Get PDFSawdust and rice husk are available in abundance and indigenous in Nigeria but have not been exploited because they cannot be used directly in combustion processes due to their loose form unless by pelleting or briquetting. This experimental study assesses the potential of pellets from sawdust (SD) and rice husk (RH). Pallet samples collected from mills were thereafter optimized in ratios (i.e. 90%RH:10%SD, 80%RH:20%SD, 70RH:30SD, 60%RH:40%SD, 50%RH:50%SD, 100%RH and 100%SD) using mixing ratio optimization model. Seven samples were produced using a manual screw press machine and were subsequently categorized in terms of calorific value (CV), proximate and ultimate analyses using the ASTM standards. Results showed that the 100%RH pellets have higher CV of 31,026.3kJ/kg and the 100%SD a value of 26,088.3kJ/kg while the optimized pellets range from 25,867.39kJ/kg to 27,063.60kJ/kg. The CV decreases with increasing ash content of the pellets. It was also observed from the proximate analysis that the 100%RH has low percentages of moisture content, volatile matter and ash content compared to others. The optimized pellets showed that SD has the tendency to reduce the sulfur content in RH; hence, a promising alternative source of energy to the conventional fossil fuel
Optimization of multiple performance responses of a fish feed pelletizer machine
Get PDFThis study details the assembling of a prefabricated fish feed pelletizing machine and optimization of some operational parameters such as die thickness, number of die holes, shaft speed and feed rate to produce high-grade fish pellets. The Taguchi methodology and Grey relational analysis (GRA) have been utilized to evaluate the multi-objective functions of interest such as pelletizing efficiency, throughput, energy requirements and pellets bulk density (g/cm3). The pelletizer machine performance evaluation test was carried at 3 levels of die thickness (8, 6 and 12 mm), number of die holes (30, 25, and 35), and feed rates (145, 130 and 160 g/h). The test for the performance indicators was conducted using L9 orthogonal array experimental design. The test data were analyzed using the Taguchi scheme employing the signal-to-noise ratio response with effects deduced. The GRA was utilized to assess multiple responses by fusing the Taguchi technique with the GRA. Thus the multi-objective optimization was transformed to a single equivalent objective function. The results of Taguchi optimization revealed that die thickness was the most influential parameter for the various control factors. In addition, optimum parameter combination was obtainable at medium die thickness (8mm), medium number of die holes (30), low shaft speed (200rpm) and medium feed rate of 145g/h. Analysis of variance for grey relational grade (GRG) reveals that die thickness and feed rate are the dominant parameters. The confirmation test performed shows that the GRG is enhanced by 2.19%
Effects of energy band structure on gallium arsenide based MOSFET
Get PDFThis research work is focused on material science and semiconductor engineering. It emphasized on the semiconductor material such as Gallium arsenide (GaAs). The Gallium arsenide semiconductor material was used as a group III-V compound for metal-oxide semiconductor field effect transistor (MOSFET) modeling. The band-gap energy structures were analyzed by using material parameters such as Varshni parameters, temperature and doping concentrations. Then, an electrical characteristic was carried out depending on the current and voltage relationship. The current flowing in the device is associated with a gate voltage applied to the device. From this paper, the analysis of MOSFET modeling was investigated using mathematical equations and MATLAB simulation