Experimental investigation and gray relational optimization of engine parameters to improve the output characteristics of an ammonia biodiesel-powered dual-fuel combustion engine

Elumalai, R. and Sumathy, S. and K, Ravi and Akhtar, Mohammad Nishat and Elumalai, P.V. and Khan, Sher Afghan and Gupta, M. Satayanarayana and Asif, Mohammad (2024) Experimental investigation and gray relational optimization of engine parameters to improve the output characteristics of an ammonia biodiesel-powered dual-fuel combustion engine. Case Studies in Thermal Engineering, 56. pp. 1-20. ISSN 2214-157X

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Abstract

An innovative approach to this research is to evaluate the effects of different concentrations of biodiesel with premixed ammonia energy in a dual-fuel combustion engine and determine the best operating conditions for optimal engine responses. Experimental results of a 40% ammonia energy premixing fraction with direct injection of a biodiesel blend of 30% (40%AEPF + B30) at 80% load improved brake thermal efficiency (BTE) by 8.42% while reducing brake specific energy consumption (BSEC) by 13.28%. It also reduces the hydrocarbon (HC) emission by 16.8%, the carbon monoxide (CO) emission by 15.06%, and the smoke opacity by 26.8%. As opposed to this, carbon dioxide (CO2) and nitrogen oxide (NOx) emissions are elevated by 21.5% and 16.54%, respectively, relative to the 40% ammonia energy premixing fraction with direct injection of diesel (40%AEPF + Diesel). Thereafter, the ANOVA technique is also utilized to analyze the impact of operational parameters, and the findings show that the responses are statistically significant. Additionally, the results are utilized in a grey relational analysis (GRA) based optimization process to determine the appropriate operational variables. According to optimization results, 40%AEPF + B30 at 80% load provides the most efficiency and fuel economy. It is capable of being used as an alternate fuel instead of conventional diesel.

Item Type:	Article (Journal)
Uncontrolled Keywords:	Engine calibrationEngine optimizationAmmonia as fuelMulti objective optimizationGrey relational analysisANOVAEngine influential factors
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ163.26 Energy conservation
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button):	Kulliyyah of Engineering > Department of Mechanical Engineering Kulliyyah of Engineering
Depositing User:	Prof. Dr. Sher Afghan Khan
Date Deposited:	14 Mar 2024 08:50
Last Modified:	14 Mar 2024 10:45
URI:	http://irep.iium.edu.my/id/eprint/111353

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