Arid Zone Journal of Engineering, Technology and Environment (AZOJETE)
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Response Surface Methodology and Artificial Neural Network Modeling and Optimization of Luffa Cylindrica Fibre Pyrolysis in a Fixed-Bed Pyrolizer
No full textBio-oil production from Luffa fibre, a plentiful agricultural byproduct, has attracted considerable interest as a sustainable and renewable energy source. In this study, response surface methodology (RSM) and artificial neural network (ANN) modelling were used to optimize operating conditions for bio-oil produced by pyrolysis from luffa cylindrica fibre. Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) are used to model and improve operational parameters like temperature, particle size diameter, and inert gas flow rate. This is done to boost bio-oil production and quality. We develop a predictive model for bio-oil characteristics using ANN modelling, which effectively optimizes pyrolysis conditions. This study offers significant knowledge on the production and characteristics of bio-oil derived from luffa cylindrica fibres. By employing both models, we leveraged Response Surface Methodology (RSM) flexibility to provide statistical measures of individual models and their interaction impact on the process output while benefiting from Artificial Neural Networks (ANN) efficiency in processing data and acquiring complex patterns. It offers a method to improve the production process methodically. Comparing the prediction findings of the ANN with those of the RSM, it was shown that the former were superior. Different models have been trained using various transfer functions and varying numbers of neurons with 0.99797, 1.0, and 0.9989 R² values for the training, validation, and test stages, respectively. The proposed network had an overall R² factor of 0.99869. The results were deemed satisfactory based on the overall R² value being near 1.0. The optimization of operational parameters enhances the effective transformation of luffa cylindrica fibre into bio-oil, therefore encouraging the utilization of this sustainable resource for the generation of renewable energy. This strategy aligns with the increasing focus on decreasing the environmental consequences of conventional fossil fuels and promoting alternative and eco-friendly energy supplies
Development of a Simulated Annealing-Optimized Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) for Sorghum Seed Planting Parameter Tuning
Get PDFPrecision agriculture requires adaptive control systems to optimize planting operations, ensuring consistent planting depth under varying soil and operational conditions. This paper proposes a novel Simulated Annealing-optimized Adaptive Neuro-Fuzzy Inference System (SA-ANFIS) controller for real-time adjustment of planting parameters based on soil moisture and planting speed. The ANFIS framework combines fuzzy logic and neural networks to model nonlinear relationships, while Simulated Annealing (SA) optimizes membership functions and rule bases to enhance control accuracy. Experimental validation demonstrates that the SA-ANFIS controller significantly improves adaptive performance compared to standalone ANFIS controllers, reducing root mean square error (RMSE) by ~18% in dynamic field conditions. The proposed system offers a robust solution for precision planting machinery, enhancing crop yield and resource efficiency. It is, therefore, recommended for autonomous planter
The Effect of Fermentation on the Proximate Composition, Physical and Functional Properties of Guna (Citrullus vulgaris) Seeds
Get PDFGuna (Citrullus vulgaris) is a type of melon seed traditionally extracted from its gourds after fermentation. This study investigated the effect of fermentation on the physical, proximate, and functional properties of guna seeds. Fresh gourds were divided into three treatments namely; control (0 day), 7-day fermentation, and 14-day fermentation and shade-dried. Standard analytical methods were employed for the analyses. The results showed that fermentation had no significant effect (P > 0.05) on seed length (6.05–6.07 mm), width (3.43–3.46 mm), thickness (1.46–1.51 mm), sphericity (0.51–0.52), arithmetic diameter (3.65–3.68 mm), geometric diameter (3.12–3.17 mm), aspect ratio (56.69–57.10), or surface area (30.54–31.48 mm²). However, 1000-seed mass (31.78–34.60 g) and bulk density (1.64–1.82 g/cm³) were significantly affected (P < 0.05), decreasing with longer fermentation time. Proximate analysis revealed moisture (4.63–4.78%), ash (3.11–3.37%), protein (23.70–29.95%), fat (25.71–28.63%), fibre (18.54–19.21%), and carbohydrate (17.67–20.72%). Fermentation significantly (P < 0.05) increased moisture, protein, and ash contents, while reducing fat, fibre, and carbohydrate values. Functional properties improved with fermentation time, including higher water absorption capacity (73.97–82.00%), oil absorption capacity (54.12–66.67%), foam capacity (17.22–21.11%), and foam stability (12.78–13.89%), alongside reduced flour bulk density (1.15–1.18 g/cm³). In conclusion, 14-days fermentation time enhanced protein and ash content, improved hydration and oil-binding properties, and lowered bulk density, indicating potential for guna seed protein supplementation in food applications
Analyzing the Spatial and Temporal Dynamics of Rainfall and Drought in The Vall River Basin, South Africa
No full textClimate change continues to have devastating effects worldwide, particularly through drought, impacting billions of people. A recent study focused on the Vaal area in South Africa, a semi-arid region reliant on the Vaal River, a vital water resource. Researchers utilized the Standardized Precipitation Index (SPI) and Standardized Precipitation and Evapotranspiration Index (SPEI) to assess rainfall variability, evapotranspiration, drought, and trends over four decades. The results show some characteristics of Rainfall Patterns; such as Peak precipitation occurs during the January to March summer months while Drought Years: 2016 was identified as a hydrologically driest year for the Vaal River based on SPI and SPEI analysis at 12- and 24-month scales. Similarly, Agricultural Drought: Years like 1983, 1999, 2016, and 2019 exhibited agricultural drought, particularly evident in SPEI/SPI -3 and SPEI/SPI -6, crucial for local irrigation and agricultural production. Furthermore, for Temporal Consistency: SPI and SPEI demonstrated increasing temporal consistency with longer timescales until 2019, except for SPEI/SPI-1 and SPEI/SPI-48, which did not accurately represent drought in the Vaal River basin. Interestingly, the study highlights the escalating impact of climate change-induced drought in the Vaal area and underscores the importance of SPEI in assessing drought severity. Therefore, as climate conditions worsen globally, such analyses are vital for informed decision-making and effective water resource management
Harnessing The Sun's Potential: An Arduino-Based System for Optimized Energy Management in PV Systems
Get PDFThe global shift towards renewable energy sources has placed photovoltaic (PV) systems at the forefront of sustainable energy solutions. Traditional PV systems often suffer from inefficiencies due to fixed load thresholds that do not adapt to changing environmental conditions, leading to energy waste. It proposes an innovative Arduino-based system for optimizing energy management in PV systems. The Arduino platform was selected for its ease of programming, affordability, and compatibility with various sensors. By continuously monitoring real-time data such as solar irradiance, battery status, and local energy consumption, the proposed system dynamically adjusts load thresholds to prevent energy waste and grid overload. The system architecture includes high-efficiency PV panels, a solar charge controller, deep-cycle batteries, and various sensors to monitor voltage, current, and temperature. The system employs deep-cycle batteries with capacities based on the energy requirements and expected usage patterns, and voltage regulators such as the LM7805 to ensure safe operation of the Arduino microcontroller at 5V, converted from the standard 12V input. This setup shows the comprehensive integration of components to ensure optimal performance. Simulation results demonstrate the system’s ability to manage power effectively, preventing overload and promoting energy efficiency. By maintaining precise control over energy distribution and utilizing a user-friendly interface for real-time monitoring, this research highlights the potential of an intelligent, cost-effective solution for enhanced energy management in PV systems, paving the way for more sustainable energy consumption
Hardness, Density and Water Absorption Properties of Doum Palm Shell Particles and Sugarcane Bagasse Reinforced Polypropylene Hybrid Composite
Get PDFAgricultural waste issues have been a subject of discussion mainly on its conversion to wealth because of some environmental problems associated with it. The use of natural fibers and agricultural wastes for the formulation of composites materials has therefore continue to receive great attention. This work is focused on the utilization of Doum Palm shell particles and Sugarcane Bagasse to reinforce polypropylene (PP) in the production of a hybrid composite. The influence of material loading on the hardness, density and water absorption properties of the composite was studied. The composites were set by compounding PP and Doum Palm shell particles using compression moulding technique. The particulate size of the filler materials considered was 150 μm. The different material loading to matrix mixture were 10:90,20:80, 30:70, 40:60 and 50:50 respectively, after which the composites were characterized. SEM analysis was also carried out in order to know the level of interaction between the matrix and materials loaded. Analyses of variance (ANOVA) were employed for optimization of the results. Hardness of neat PP was 65Hv but gradually decreased with material loading to a value of 42.3Hv at 50wt% loading of the PP. Water absorption showed a direct proportionality with exposure time and fiber loading up to 8.49% after 14days of soaking. Material loading ensured increased density proportionally to 0.468g/cm3 at 50 wt%. The optimization result showed significant difference in most of the results obtained. It is concluded that Doum Palm shell and Sugarcane Bagasse hybrid composites have potential for industrial application
Electrical Resistivity Survey for Groundwater Investigation in Parts of Osun State, Southwestern Nigeria
Get PDFThis study used a non-invasive, cost-effective geophysical method for locating suitable sites for groundwater development. Thirty-two Vertical Electrical Sounding (VES) were probed in the investigated area using Schlumberger array. The data acquired were interpreted using the partial curve matching technique and computer-aided iteration through WINRESIST. The aquifer properties such as transverse resistance, longitudinal conductance, hydraulic conductivity and transmissivity were computed from the primary geoelectric parameters. The results of the study revealed that the investigated area is marked by heterogeneous lithology with three to five geoelectric layers. The aquifer resistivities ranged from 18 to 318 Ωm while the aquifer thicknesses ranged from 1.7 to 46.2 m. The computed transverse resistance revealed the groundwater development in the investigated area as low/moderate. Also, the transmissivity values computed from the primary aquifer parameters revealed that 72% of the investigated area has low aquifer transmissivity, while 28% have moderate aquifer transmissivity. This implies that the investigated area has low/moderate water-bearing potentiality. The quantitative analysis of the aquifer protective rating revealed that 78.1% of the investigated area has a good natural filter. Based on the aquifer potential rating and the protective capacity, VESes 10-12, 16, 19-20, 23-25 were recommended for drilling sites. The result of this study provides some important conclusions for future groundwater exploration and management in the investigated area
Groundwater Contamination Risk Assessment: Pahs Pollution from Crude Oil Leaching in Ogbia, Bayelsa State
Get PDFGroundwater is the largest reservoir of drinkable water, accounting for approximately 22% of the world’s freshwater. However, regular crude oil spills have resulted in severe groundwater contamination by Polycyclic Aromatic Hydrocarbons (PAHs), which harm human health and the environment. This investigated the presence and concentration of PAHs in groundwater in Ibelebiri in Ogbia, Bayelsa State, Nigeria, following an oil spill, to determine contamination pathways and potential consequences. Soil samples were taken from three locations (L1, L2, L3) and three depths (topsoil, subsoil, and aquifer) and examined for PAHs such as Naphthalene, Acenaphthene, Fluorene, Pyrene, Anthracene, and Benzo(a)anthracene. Laboratory results found that Naphthalene had the highest concentration in all samples, particularly topsoil, whereas heavier PAHs such as Pyrene and Anthracene had lower quantities, notably in aquifer samples. The Leach Pollution Index (LPI) ranged from 81,199.25 to 83,374.10, indicating a high level of contamination potential. Statistical analysis using ANOVA revealed significant variation in the concentrations of lighter PAHs such as Naphthalene (P-value = 0.00059193) and Fluorene (P-value = 0.002376112) between soil layers, while heavier PAHs such as Pyrene (P-value = 0.969122843), Anthracene (P-value = 0.984906863), and Benzo(a)anthracene (P-value = 0.358155023) showed no significant differences across the samples. The findings underline the necessity for focused remediation measures to mitigate groundwater contamination while safeguarding public health and environmental quality
The Impact of Stator Tooth and Pole Combinations on Output of a Dual Stator Electric Machine
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Optimization of Arc Welding Parametric Influence on Mechanical Properties of Dissimilar Metals
Get PDFWelding dissimilar metals require technical expertise to achieve moderate cost, quantity, and quality, but selecting the right parameters is challenging due to various operating conditions. The paper optimized welding process parameters for two dissimilar metals, INCONEL 625 and GL E360, focusing on mechanical properties like tensile strength and hardness. The welding process parameters were optimized using Gas Metal Arc Welding power sources, Flux Cored Wire Electrode (FCWE), design experts, and response surface methodology, and tensile strength and hardness tests were conducted. At the anticipated optimal process welding parameters of 52.86 m/s welding speed, 5.28 m/min welding feed rate, and 23.16 volts, three confirmation experiments were carried out. The study revealed that the tensile strength and hardness of the welding process significantly influenced response variables, ranging from 380 MPa to 500 MPa. The most noticeable effect was observed at a welding speed of 52 m/s, a feed rate of 5.6 m/min, and a voltage of 26 V. The empirical model's tensile strength and hardness were validated using experimental results, and the software predicted 53 welding speed, 5 welding feed rate and 23 voltages. The welding process parameters significantly impacted tensile strength and hardness, while the welding feed rate parameter had the least impact on both.