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A COMPARATIVE COMPUTATIONAL INTELLIGENCE APPROACH FOR HEAT TRANSFER ANALYSIS OF CORRUGATED PLATE HEAT EXCHANGERS

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dc.creator İPEK, Osman
dc.creator Sahin, Arzu Sencan
dc.creator KILIÇ, BAYRAM
dc.date 2018-07-31T21:00:00Z
dc.date.accessioned 2020-10-06T09:48:52Z
dc.date.available 2020-10-06T09:48:52Z
dc.identifier 437564f5-9c65-44e7-af93-40a81895e821
dc.identifier 10.30638/eemj.2018.182
dc.identifier https://avesis.sdu.edu.tr/publication/details/437564f5-9c65-44e7-af93-40a81895e821/oai
dc.identifier.uri http://acikerisim.sdu.edu.tr/xmlui/handle/123456789/58617
dc.description In this paper, an application artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are presented to predict the heat transfer rate and effectiveness in the corrugated plate heat exchangers. First, the thermal performances of the corrugated plate heat exchangers were evaluated experimentally. Experimental data were used for training and testing network. The results of the ANN are compared with the ANFIS in which the same data sets are used. The ANN model is slightly better than ANFIS. The coefficient of multiple determination (R-2) values obtained when unknown data were used to the networks were 0,999636 for heat transfer rate and 0,999565 for effectiveness, which is very satisfactory. This demonstrates that the neural network presented can help the engineers and manufacturers predict the thermal characteristics of corrugated plate heat exchangers under various operating conditions.
dc.language eng
dc.rights info:eu-repo/semantics/closedAccess
dc.title A COMPARATIVE COMPUTATIONAL INTELLIGENCE APPROACH FOR HEAT TRANSFER ANALYSIS OF CORRUGATED PLATE HEAT EXCHANGERS
dc.type info:eu-repo/semantics/article


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