Composites are driving positive developments in the automobile sector. In this study investigated the use of composite fins in radiators using computational fluid dynamics (CFD) to analyze the fluid-flow phenomenon of nanoparticles and hydrogen gas. Our world is rapidly transforming, and new technologies are leading to positive revolutions in today's society. In this study successfully analyzed the entire thermal simulation processes of the radiator, as well as the composite fin arrangements with stress efficiency rates. The study examined the velocity path, pressure variations, and temperature distribution in the radiator setup. As found that nanoparticles and composite fins provide superior thermal heat rates and results. The combination of an aluminum radiator and composite fins in future models will support the control of cooling systems in automotive applications. The final investigation statement showed a 12% improvement with nanoparticles, where the velocity was 1.61 m/s and the radiator system's pressure volume was 2.44 MPa. In the fin condition, the stress rate was 3.60 N/mm2.
Accelerating population and modernization has triggered a steady rise in energy demand and a significant rise in household waste, particularly municipal solid waste. In this context, waste-to-energy conversion has emerged as a sustainable solution. This study aims to maximize biofuel production yield using biomass-based banana peel catalyst waste by optimizing process parameters through machine learning models integrated with k-fold cross-validation. The models employed include Polynomial Regression (PR), Decision Tree (DT), Random Forest (RF), and Linear Regression (LR). The three key input variables including reaction temperature (RT), catalyst concentration (CC), and methanol-to-oil molar ratio (MOR) were used to train and test the models, with biodiesel yield as the measured output. Among the models, PR emerged as the best-performing one for predicting biofuel yield, demonstrated by its high R² value of 0.956 and low error metrics (RMSE = 1.54 MSE = 2.39 MAE = 1.43). The best model was determined through balancing bias and variance across k-fold validation iterations, where PR exhibited the highest average R² value of 0.868. Furthermore, the optimized process parameters predicted by PR for maximum biofuel yield were a RT of 59°C, CC of 2.96%, and a MOR of 9.21, resulting in a yield of 95.38%. These findings contribute to advancing large-scale machine learning-driven biofuel optimization, supporting industrial waste-to-energy applications, and fostering sustainable energy development.
The traditional approach of open-sun drying is facing contemporary challenges arising from the widespread adoption of energy-intensive methods and the quality of drying. In response, solar dryers have emerged as a sustainable alternative, utilizing solar thermal energy to effectively dehydrate vegetables. This study investigates the performance of a single-basin, double-slope solar dryer utilizing natural convection for drying bottle gourds and tomatoes, presenting a sustainable alternative to traditional open-sun drying. The solar dryer exhibited superior moisture removal efficiency, achieving a 94.42% reduction in tomatoes and 83.87% in bottle gourds, compared to open-sun drying. Drying rates were significantly enhanced, with maximum air and plate temperatures reaching 54.42 °C and 63.38 °C, respectively, accelerating the dehydration process. Moisture diffusivity analysis revealed a marked improvement in drying behavior under solar drying, with values ranging from 3.12 × 10-11 to 4.31 × 10-11 m2/s for bottle gourds, and 4.65 × 10-11 to 2.31 × 10-11 m2/s for tomatoes. Energy efficiency assessments highlighted the solar dryer's advantage, with exergy efficiency peaking at 61.78% for bottle gourds and 68.5% for tomatoes. Furthermore, the activation energy required for drying was significantly lower in the solar dryer (29.14-46.41 kJ/mol for bottle gourds and 27.16-55.42 kJ/mol for tomatoes) compared to open-sun drying, enhancing energy conservation. Visual inspections confirmed the superior quality of the solar-dried vegetables, free from dust and impurities. An economic analysis underscored the system's viability, with payback periods of 2 years for bottle gourds and 1.6 years for tomatoes. Overall, this study demonstrates the efficacy of solar dryers in optimizing vegetable preservation while promoting energy efficiency, aligning with global sustainability goals by reducing post-harvest losses and supporting eco-friendly practices.