Photothermal solar assisted Madhuca diethyl ether fuel processing for LHR engines with AI-based performance and yield prediction

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dc.contributor.authorRakesh Dubey
dc.contributor.authorAjeet Kumar Prajapati
dc.contributor.authorShruti Bharadwaj
dc.contributor.authorViroon Kamchoom
dc.contributor.authorKennedy C. Onyelowe
dc.contributor.authorKrishna Prakash Arunachalam
dc.date.accessioned2026-05-08T19:26:35Z
dc.date.issued2026-3-20
dc.description.abstractemissions. Heat release rate analysis indicated earlier and more efficient combustion behavior. Additionally, LSTM-based predictive modeling showed lower error margins compared with RNN, demonstrating improved prediction accuracy for engine performance parameters.
dc.identifier.doi10.1038/s41598-026-44697-w
dc.identifier.urihttps://dspace.kmitl.ac.th/handle/123456789/20694
dc.publisherScientific Reports
dc.subjectBiodiesel Production and Applications
dc.subjectSolar Thermal and Photovoltaic Systems
dc.subjectSolar-Powered Water Purification Methods
dc.titlePhotothermal solar assisted Madhuca diethyl ether fuel processing for LHR engines with AI-based performance and yield prediction
dc.typeArticle

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