Multi-objective optimization of a diesel engine fueled with different fuel types containing additives using grey-based Taguchi approach

dc.authoridMehregan, Mina/0000-0002-3127-2565
dc.contributor.authorCelik, Mehmet
dc.contributor.authorBayindirli, Cihan
dc.contributor.authorMehregan, Mina
dc.date.accessioned2024-11-07T13:34:33Z
dc.date.available2024-11-07T13:34:33Z
dc.date.issued2022
dc.departmentNiğde Ömer Halisdemir Üniversitesi
dc.description.abstractDue to the reduction of fossil fuels' resources and their contribution to environmental problems, biodiesel fuels have attracted significant attention as substitutes for diesel fuels. However, since their NOx emissions are higher than that of diesel fuels in most cases and also because of their higher viscosity than diesel, fuel additives are used to enhance their properties and reduce emissions. In this study, the effect of n-hexane and n-hexadecane addition to biodiesel and diesel fuels on exhaust emissions and performance of a single-cylinder diesel engine was investigated by using grey-based Taguchi method. Fuel additive, the additive amount, and fuel type were considered as the operating parameters. Three fuel types including diesel, rapeseed oil biodiesel, and cottonseed oil biodiesel were used in this investigation, while n-hexane and n-hexadecane were considered as the two fuel additives. As well as, three levels were assigned to the additive amount which were 4, 8, and 12%. Based on the operating parameters and their levels, the plan of experiments was generated according to L-18 orthogonal array. Using grey relational analysis, this multi-response optimization problem was first transformed into a single response optimization. Then, this single system response, which is known as grey relational grade, was utilized in Taguchi approach for statistical evaluations. The results demonstrated that rapeseed was the best selection for fuel type compared to cottonseed and diesel in order to have the optimum system responses and hexadecane gave better results for system optimization in comparison with hexane additive. As well as, the analysis of variance showed that fuel type was the predominant operating factor influencing the grey relational grade which means fuel type was the most important parameter in the simultaneous optimization of exhaust emissions and engine performance. The Taguchi results also revealed that the optimum condition of engine performance and exhaust emissions happened when engine was fueled with rapeseed biodiesel containing 12% hexadecane as an additive. The confirmation test result validated the reliability of Taguchi approach in this investigation.
dc.identifier.doi10.1007/s11356-021-18012-1
dc.identifier.endpage30284
dc.identifier.issn0944-1344
dc.identifier.issn1614-7499
dc.identifier.issue20
dc.identifier.pmid34997500
dc.identifier.scopus2-s2.0-85122501130
dc.identifier.scopusqualityQ1
dc.identifier.startpage30277
dc.identifier.urihttps://doi.org/10.1007/s11356-021-18012-1
dc.identifier.urihttps://hdl.handle.net/11480/16049
dc.identifier.volume29
dc.identifier.wosWOS:000740214300001
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.indekslendigikaynakPubMed
dc.language.isoen
dc.publisherSpringer Heidelberg
dc.relation.ispartofEnvironmental Science and Pollution Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241106
dc.subjectBiodiesel
dc.subjectFuel additive
dc.subjectMulti-objective optimization
dc.subjectExhaust emission
dc.subjectTaguchi method
dc.subjectGrey relational analysis
dc.titleMulti-objective optimization of a diesel engine fueled with different fuel types containing additives using grey-based Taguchi approach
dc.typeArticle

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