Investigation of a ternary blend of diesel/ethanol/n-butanol with binary nano additives on combustion and emission: A modeling and optimization approach with artificial neural networks

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dc.contributor.authorAtelge, M. R.
dc.date.accessioned2024-12-24T19:27:08Z
dc.date.available2024-12-24T19:27:08Z
dc.date.issued2022
dc.departmentSiirt Üniversitesi
dc.description.abstractThe increase in global energy consumption and concerns about fossil fuels depletion are pushing the demand for renewable and clean energy sources. Alcohols are a promising candidate for internal combustion engines as alternative fuels. This study aims to reveal the effect of a ternary blend, which is denominated D80E10nB10, consisting of diesel (80%), ethanol (10%), and n-butanol (10%) on combustion and emission characteristics. The addition of both metal oxide (TiO2) and nonmetallic nanoparticle (MWCNT) was also investigated with the above-mentioned ternary blend fuels, which are denominated m- . The compression ignition engine was run under dual fuel mode with feeding H-2 in the range of 5 and 15 g/h, which were labeled D80E10nB10H5 and 15. The results revealed that the maximum pressure increased by 3.63 and 3.94% by adding 5 and 15 g/h H-2 respectively into ternary blend fuel under the full load. The highest BTE was obtained from modified diesel fuel which was 23.24% higher than diesel. Furthermore, 60 Artificial Neural Network (ANN) models were built to optimize test conditions. The optimal conditions for ternary blend fuel were found to be 4 g/h H-2 feeding rate while 5.5 g/h H-2 addition with modified ternary blend fuel would be the optimal.
dc.identifier.doi10.1016/j.fuproc.2021.107155
dc.identifier.issn0378-3820
dc.identifier.issn1873-7188
dc.identifier.scopus2-s2.0-85123989424
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.fuproc.2021.107155
dc.identifier.urihttps://hdl.handle.net/20.500.12604/6522
dc.identifier.volume229
dc.identifier.wosWOS:000791326600003
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofFuel Processing Technology
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_20241222
dc.subjectNano additive
dc.subjectTiO (2) and MWCNT
dc.subjectHydrogen
dc.subjectN-Butanol
dc.subjectOptimization with ANN model
dc.titleInvestigation of a ternary blend of diesel/ethanol/n-butanol with binary nano additives on combustion and emission: A modeling and optimization approach with artificial neural networks
dc.typeArticle

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