Effect of α-aluminium oxide nano additives with Sal biodiesel blend as a potential alternative fuel for existing DI diesel engine - Abhishek Sharma, Abhishek Sharma; Harveer Singh Pali, Harveer Singh Pali; Manish Kumar, Manish Kumar; Nishant Kumar Singh, Nishant Kumar Singh; Erween Abd Rahim, Erween Abd Rahim; Yashvir Singh, Yashvir Singh; Naveen Kumar Gupta, Naveen Kumar Gupta
The increasing demand, rapid consumption, price increase, limited reserves, and environmental concern due to pollution produced by conventional fossil fuel (diesel & gasoline) are a few reasons why biofuels need to be explored. The present paper employs a systematic methodology to examine the performance of a 20% volumetric blend of Sal biodiesel (S20) blended with diesel using αaluminium oxide (α-Al2O3) nanoparticles (NP) as additives and is compared with a diesel under like circumstances. The central composite design, Box-Behnken design (BBD) based response surface methodology, and desirability tests are used in the organized experiments on a diesel engine configuration to facilitate calibration. The created multivariate regression model yields all of the best engine inputs. Interaction effects are used to determine the most influential element by observing the interaction of two distinct input factors on a single response. According to the desirability tests, the highest estimated desirability was 0.579; the optimal input parameters found are 21°bTDC injection timing (IT), 238 bar injection pressure (IOP), 17 compression ratio (CR), and 74 ppm concentration of α-Al2O3NP, estimated the optimized response of brake thermal efficiency (BHTE) 31.18%, brake specific fuel consumption (BSFC) 0.2975 kg/kWh, carbon monoxide (CO) 0.0887%, hydrocarbon (HC) 31 ppm, oxide of nitrogen (NOx) 677 ppm, and smoke level 54.92%. These predicted values were validated with experimental results, and errors were within the range. The nanoparticle combination sample offers improved brake thermal efficiency (BTHE) and lower BSFC rate than the S20 while testing for the optimal parametric condition.