This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel engine.The dispersion of Al_(2)O_(3...This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel engine.The dispersion of Al_(2)O_(3)nanoparticles in B20 blends at different concentrations was done with the help of ultrasonicator.Good number of blends were prepared for the analysis.Advanced Machine learning algorithms(Random Forest(RF)and CatBoost)was used for the prediction.The results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with nanoparticles.But these Fuel blends have higher calorific values.These blends exhibited reduced Brake Specific Fuel Consumption(BSFC)of 2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%(in volume),DSMEB20),57.14%less CO,40.8% less hydrocarbon,and increased NO_(x)emissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with nanoparticles.DSME B20NP30 is the optimal blend for performance and emission characteristics.The study concludes with findings on enhanced Brake Thermal Efficiency(BTE)of 26.29% in 3×10^(-5)(in volume)Al_(2)O_(3)nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle concentration.The correlation matrix shows how engine load,efficiency measures(BTE,BSFC),and emissions(CO,CO_(2),NO_(x),Smoke)are connected in complex ways.The results help us understand the complicated dynamics of engine performance and emission characteristics better.Taylor's diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing phase.Similar results were obtained for CO and CO_(2)emission results.展开更多
基金the support provided by Researchers Supporting Project Number RSP2024R424,King Saud University,Riyadh,Saudi Arabia。
文摘This study investigates the effect of aluminium oxide nanoparticlesaddition to biodiesel blends made from dairy milk scum on performance and combustion characteristics of the diesel engine.The dispersion of Al_(2)O_(3)nanoparticles in B20 blends at different concentrations was done with the help of ultrasonicator.Good number of blends were prepared for the analysis.Advanced Machine learning algorithms(Random Forest(RF)and CatBoost)was used for the prediction.The results show that in comparison to biodiesel blends without nanoparticles,the kinematic viscosity and density is higher for fuel blends with nanoparticles.But these Fuel blends have higher calorific values.These blends exhibited reduced Brake Specific Fuel Consumption(BSFC)of 2.85% than the blends without nano particles(Dairy Scum Methyl Ester Biodiesel 20%+Neat Diesel 80%(in volume),DSMEB20),57.14%less CO,40.8% less hydrocarbon,and increased NO_(x)emissions compared to conventional diesel,contributing to the development of environmentally friendly and renewable biofuel blends with nanoparticles.DSME B20NP30 is the optimal blend for performance and emission characteristics.The study concludes with findings on enhanced Brake Thermal Efficiency(BTE)of 26.29% in 3×10^(-5)(in volume)Al_(2)O_(3)nanoparticle-blended DSME B20 and other DSME B20 fuel blends,emphasizing the importance of optimal nanoparticle concentration.The correlation matrix shows how engine load,efficiency measures(BTE,BSFC),and emissions(CO,CO_(2),NO_(x),Smoke)are connected in complex ways.The results help us understand the complicated dynamics of engine performance and emission characteristics better.Taylor's diagram for BTE and BSFC shows that CatBoost-based BTE models perform superior to RF-based models during the training as well as testing phase.Similar results were obtained for CO and CO_(2)emission results.
