Diesel engine vibration analysis using artificial neural networks method: Effect of NH3 additive in biodiesels

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dc.contributor.authorRaja Ahsan Shah, Raja Mazuir
dc.contributor.authorBöyükdipi, Ömer
dc.contributor.authorTüccar, Gökhan
dc.contributor.authorAl-Otoom, Awni
dc.contributor.authorSoyhan, Hakan Serhad
dc.date.accessioned2025-01-06T17:30:10Z
dc.date.available2025-01-06T17:30:10Z
dc.date.issued2024
dc.description.abstractDiesel engine parameters, such as fuel and its additives, play an essential role in minimising the effects of engine vibration. This study aimed to use artificial neural networks (ANN) to model and analyse diesel engine vibration characteristics at different engine speeds using NH3 as an additive in hazelnut (HD), peanut (PD), and waste-cooking oil (WD) biodiesels. The results showed good correlations between the ANN models and experimental results using regression analysis methods. The ANN models for diesel engines showed high accuracy. The ANN models indicated that a 5 % NH3 additive decreased engine vibration for HD and PD. In comparison, 10 % and 15 % NH3 additive ratios increased engine vibration for HD, PD, and WD due to low combustion quality. The lowest vibration levels occurred with P100, P95A5, P90A10, and P85A15 at 1200 rpm. H100 and H95A5 produced the highest diesel engine resultant vibration (DERV) values. All ANN models generated the lowest and highest DERV values at 1200 rpm and 2100 rpm, respectively. The RMS method showed that H95A5, P85A15, and W85A15 contributed the most to diesel engine vibration. Using a low amount of NH3 additive positively affected DERV for HD and PD but not for WD. © 2024
dc.description.sponsorshipQatar National Library, QNL
dc.identifier.doi10.1016/j.treng.2024.100254
dc.identifier.issn2666-691X
dc.identifier.scopus2-s2.0-85193788025
dc.identifier.scopusqualityQ1
dc.identifier.urihttps://doi.org/10.1016/j.treng.2024.100254
dc.identifier.urihttps://hdl.handle.net/20.500.14669/1499
dc.identifier.volume16
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Ltd
dc.relation.ispartofTransportation Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_20241211
dc.subjectANN
dc.subjectBiodiesel
dc.subjectDiesel vibration
dc.subjectEngine modelling
dc.titleDiesel engine vibration analysis using artificial neural networks method: Effect of NH3 additive in biodiesels
dc.typeArticle

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