Machine learning and response surface optimization to enhance diesel engine performance using milk scum biodiesel...

This study investigates the impact of incorporating aluminum oxide (Al₂O₃) nanoparticles into biodiesel blends derived from dairy scum methyl ester (DSME) on the performance and emission characteristics of a diesel engine. A total of five fuel blends were prepared for experimental evaluation: neat diesel, DSMEB10 (10% DSME + 90% diesel), DSMEB20, and two nano-additized variants of DSMEB10 and DSMEB20 with 50 ppm and 60 ppm concentrations of Al₂O₃ nanoparticles, respectively. The nanoparticles were dispersed using ultrasonication to ensure homogeneous mixing. Experimental findings indicate that the blend DSMEB10 + 50 ppm Al₂O₃ achieved the highest brake thermal efficiency (BTE) of 29.1%, which is nearly equivalent to that of conventional diesel (30%). This blend also exhibited the lowest specific fuel consumption (SFC) at 0.31 kg/kWh, owing to its calorific value being comparable to diesel, thereby enhancing fuel utilization. In terms of emissions, DSMEB100 + 50 ppm demonstrated a 40% reduction in overall pollutants compared to diesel + 50 ppm, attributed to enhanced oxygen content and improved combustion kinetics. Carbon dioxide emissions were significantly lower for DSMEB10 + 50 ppm (5.5% by volume) compared to diesel + 50 ppm (7.5%), indicating a 36.3% reduction. Furthermore, nitrogen oxide (NO_x) emissions were minimized at 850 ppm for DSMEB10 + 50 ppm due to accelerated combustion and reduced high-temperature residence time, facilitated by the oxygen-rich biodiesel composition. Additionally, machine learning models were employed to predict and analyze the relationship between engine load, thermal efficiency, and emissions. Among the models tested, linear regression (LR) yielded a marginally lower mean squared error (MSE = 3.04) compared to Huber regression (MSE = 3.13), while the mean absolute error (MAE) for LR was 1.33 against 1.37 for Huber regression, suggesting LR's slightly better predictive accuracy. These findings highlight the potential of nano-enhanced DSME biodiesel blends as a sustainable and cleaner alternative to conventional diesel, with favorable engine performance and emission profiles.