Optimization of performance and emission outputs of a CI engine powered with waste fat biodiesel: A detailed RSM, fuzzy multi-objective and MCDM application

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dc.authoridEl-Shafay, A.S./0000-0002-7261-6686en_US
dc.authoridEl Shafay, A.S./0000-0003-3812-8723en_US
dc.authoridAgbulut, Umit/0000-0002-6635-6494en_US
dc.authorscopusid57218318204en_US
dc.authorscopusid58995158300en_US
dc.authorscopusid57202959651en_US
dc.authorscopusid55212662000en_US
dc.authorwosidAttia, El-Awady/D-5288-2012en_US
dc.authorwosidEl-Shafay, A.S./ABM-2263-2022en_US
dc.authorwosidEl Shafay, A.S./ABG-3271-2021en_US
dc.contributor.authorEl-Shafay, A. S.
dc.contributor.authorGad, M. S.
dc.contributor.authorAgbulut, Umit
dc.contributor.authorAttia, El-Awady
dc.date.accessioned2024-08-23T16:04:50Z
dc.date.available2024-08-23T16:04:50Z
dc.date.issued2023en_US
dc.departmentDüzce Üniversitesien_US
dc.description.abstractDecreasing the influence of diesel engines on the environment by mitigating harmful exhaust emissions is a real-life target to reach a cleaner atmosphere. Accordingly, the present work aims to reduce emissions while pre-serving enhanced performance in the diesel engine. From this point of view, the biodiesel from chicken fats was produced with the following of esterification as transesterification processes, then its mixtures with conventional diesel fuel were comprehensively investigated. A diesel engine was experimentally tested at varying engine speeds and loads. Both response surface methodology (RSM) and fuzzy multi-objective modeling techniques were used to predict the engine performance, and exhaust pollutants of diesel engine fueled with chicken biodiesel blends. Central composite RSM was used for the experimental design. Different responses were modeled mathematically via highly statistically significant models. A nonlinear fuzzy-multi-objective optimization model was also constructed and optimally solved in the paper. The multi-objective optimized results show that the blending ratio of 24.42%, engine load of 64.1%, and engine speed of 2616.6 rpm were the optimum operating conditions for the different performance and emission concentrations. These results were validated experimen-tally and the relative error was within & PLUSMN;6.67%. Sensitivity analysis was handled for the discussion of the model performance under the different importance of the performance and emission criteria. The model is capable to satisfy the decision maker's needs and gives the corresponding operating conditions. In the results, it is well-noticed that RSM, fuzzy multi-objective, and multi-criteria decision-making (MCDM) supports are good tools to both predict, and optimize the engine behaviors.en_US
dc.identifier.doi10.1016/j.energy.2023.127356
dc.identifier.issn0360-5442
dc.identifier.issn1873-6785
dc.identifier.scopus2-s2.0-85152452376en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.energy.2023.127356
dc.identifier.urihttps://hdl.handle.net/20.500.12684/14382
dc.identifier.volume275en_US
dc.identifier.wosWOS:001053867900001en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofEnergyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectPerformanceen_US
dc.subjectEmissionsen_US
dc.subjectBiodieselen_US
dc.subjectRSMen_US
dc.subjectFuzzy multi-objectiveen_US
dc.subjectMCDMen_US
dc.subjectDiesel Fuel Blendsen_US
dc.subjectExhaust Emissionsen_US
dc.subjectRendering Faten_US
dc.subjectVegetable-Oilen_US
dc.subjectAnimal Fatsen_US
dc.subjectChickenen_US
dc.subjectCombustionen_US
dc.subjectPredictionen_US
dc.subjectPressureen_US
dc.titleOptimization of performance and emission outputs of a CI engine powered with waste fat biodiesel: A detailed RSM, fuzzy multi-objective and MCDM applicationen_US
dc.typeArticleen_US

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