Engine characteristics analysis of chaulmoogra oil blends and corrosion analysis of injector nozzle using scanning electron microscopy/energy dispersive spectroscopy. (15th December 2018) - Krishnamoorthi, M.; Malayalamurthi, R.
Abstract: This work describes the performance, combustion and emission behavior of chaulmoogra oil blend and neat diesel in the variable compression ratio, variable speed compression ignition engine with exhaust gas recirculation (EGR). Exergy analysis was employed to investigate availability shares involved in the research engine. Artificial neural network (ANN) modeling and particle swarm optimization (PSO) are adopted with response surface methodology (RSM) in order to investigate the engine performance fuelled with ternary blend (65% diesel+25% chaulmoogra oil+10% diethyl ether) and neat diesel. In this work, compression ratio (CR) is varied from 14.5 to 20.6, engine speed varied from 1500 to 2400 revolution per minute (rpm) and EGR varied from 0 to 30%. The optimized condition was observed as 10% EGR, 18.1CR and 1672 rpm with respect to lesser exhaust emissions and enhanced thermal efficiency. Maximum brake thermal efficiency of 29.12% was observed 10% EGR rate and maximum exergy efficiency of 52.64% was observed for the ternary blend at the optimized engine condition. The results conclude that the RSM-ANN-PSO provide better the engine performance modeling with acceptable accuracy. The corrosion and wear analyses were done on the fuel injector nozzle and cylinder gaskets using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). Highlights: Maximum BTE of 29.12% was obtained at 20.6 CR, 1800 rpm with 10% EGR rate. Minimum NOx and HC of 176 ppm and 55 ppm were observed at 30% and 0% EGR respectively. Exergy efficiency was found to be 52.64% for the blend and 52.48% for neat diesel. ANN prediction R-value lies above 0.98 and less than 5% error in PSO-PSM algorithms. SEM/EDS analysis, corrosion and wear on nozzle tip were higher for biofuel blends.