Optimization of CeO₂ and MgO nano‐particle‐added mango seed biodiesel blends using hybrid deep belief network‐coupled sandpiper optimizer

Abstract

The ultimate goal of this study is to find a better method for minimizing hazardous emissions from a diesel engine. For this reason, emission parameters such as smoke, nitrogen oxides (NOX), unburned hydrocarbons, and carbon monoxide from a single‐cylinder diesel engine were analyzed using various biodiesel blends. The biodiesel was extracted from mango seed oil through trans‐esterification and combined with pure diesel at a 2:8 ratio. The prepared biodiesel (MSME20) was further mixed with 50, 100, and 150 ppm of either cerium oxide (CeO2) or magnesium oxide (MgO) nano‐particles through ultra‐sonication to prepare various fuel blends. The results reported that the addition of nano‐particles significantly lowered CO, HC, and smoke opacity by 25%, 25%, and 28% when compared with diesel. Also, there was a nearly 16% brake thermal efficiency gain from 50 ppm nano‐particle‐added MSME20 than pure MSME20. But for NOX emission, MSME20 fuel produced 106 ppm more NOX than diesel. Later, it was reduced up to 24 ppm while adding 50 ppm nano‐particles into MSME20 fuel. Further, a hybrid deep belief network‐coupled sandpiper optimizer was developed to optimize fuel blends. The proposed algorithm showed 37.5 ppm nano‐particle added 17.5% MSME as an optimal mix for the tested engine while running with 50% load.