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• W4366765199 abstract "Restoring a healthy environment and meeting the nation's expanding energy demand requires an uninterrupted renewable energy supply with efficient technology. One of the most effective technologies for producing gaseous fuel and subsequent electricity is the gasification of waste biomass. But the seasonal interruption of biomass waste availability creates a discontinuity in power production in the Gasifier-Engine-Genset system. Also, the different types and quantities of biomass in rural areas vary from location to location, producing different producer gas (PG) qualities. Thus, there is a need to identify its potential. Therefore, this study aims to analyze how the PG production from the gasification of Mahua wood, Sawdust briquette, and Coconut-shell affects dual-fuelled mode engine performance. To do this, Gasifier-engine experiment was conducted with operating parameters of engine brake power (BP) and compression ratio (CR) at a favorable gasification equivalence ratio (GER). Response Surface Methodology (RSM) was applied to predict optimal operating parameters for maximum engine performance and minimum emissions. RSM resulted in the optimum setting of 16.04–16.34 CR and 2.78–3.20 kW BP for maximum efficiency and diesel saving (DS). The briquette-PG-based DF engine offers maximum Brake thermal efficiency (BTE) of 25%. However, 24% BTE of coconut shell based-PG DF engine offers 57.83% maximum DS. And, respective optimum output responses were found to be 0.3223 kg/kWh Brake specific diesel consumption (BSDC), 0.0636% vol. CO, 16.73 ppm HC, 1.51%vol. CO2, and 8.19 ppm NOx. In summary, these biomass gasifications with engine integration have the potential to replace diesel with the lowest possible exhaust emissions." @default.
• W4366765199 created "2023-04-24" @default.
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• W4366765199 date "2023-09-01" @default.
• W4366765199 modified "2023-10-13" @default.
• W4366765199 title "Gasification of Briquette, Mahua wood, and Coconut shell and application to CI engines: Comparative performance and optimisation analysis" @default.
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• W4366765199 doi "https://doi.org/10.1016/j.indcrop.2023.116758" @default.
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