Publication: Substitution of diesel fuel in conventional compression ignition engine with waste biomass-based fuel and its validation using artificial neural networks
Date
2023
Authors
Ramalingam K.
Venkatesan E.P.
Vellaiyan S.
Mukhtar A.
Sharifpur M.
Yasir A.S.H.M.
Saleel C.A.
Journal Title
Journal ISSN
Volume Title
Publisher
Institution of Chemical Engineers
Abstract
This study aims to derive bioenergy from waste lather fat and citronella grass. Lather fat oil (LFO), citronella grass oil (CGO), a mixture of leather fat oil and citronella grass oil (LFCGO), and a nano-additive-incorporated mixture of lather fat oil and citronella grass oil (NFCO) were synthesized and used in diesel engines as the novelty of this study. ASTM standards were used to investigate and guarantee the fuel's properties. According to the experimental report, the nanoadditive's brake thermal efficiency and brake-specific fuel consumption were more comparable to diesel fuel. Compared to diesel, the NFCO blend reduced hydrocarbon, carbon monoxide, and particulate emissions by 6.48%, 12.33%, and 16.66%, respectively, while carbon dioxide and oxides of nitrogen emissions increased. The experiment's outcomes were verified using an artificial neural network (ANN). The trained model exhibits a remarkable coefficient of determination of 98%, with high R values varying from 0.9075 to 0.9998 and low mean absolute percentage error values ranging from 0.97% to 4.24%. Based on the experimental findings and validation report, it can be concluded that NFCO is an efficient diesel fuel substitute. � 2023 The Authors
Description
Keywords
Lather fat oil , Nano additive , NOx emission , Peel oil , Waste to energy , ASTM standards , Biodiesel , Biomass , Brakes , Carbon dioxide , Carbon monoxide , Diesel engines , Fuel additives , Neural networks , Thermal efficiency , Bio-energy , Biomass-based fuels , Compression ignition engine , Lather fat oil , Nano additives , NOx emissions , Peel oil , Synthesised , Waste biomass , Waste to energy , Diesel fuels