International Scientific Journal


Manufacturing simulation is an encouraging field in every manufacturing industry. The manufacturing simulation facilitate to virtually analysis the performance of the product before manufacturing. So for most of the manufacturing activities are simulated effective and researchers have developed adequate tool for the simulation of various activities of manufacturing. Heat exchanger is one of the important devices used for the purposes including medical, food processing, air conditioning system, etc. Performance of these heat exchangers also important for achieving better performance in those fields. So simulation of heat exchanger gives more beneficial to the engineers to analysis its performance before manufacturing. Hence in this paper, a machine learning approach for the modelling and simulation of heat exchanger is proposed. The proposed technique uses support vector machine technique for the prediction of performance of the heat exchanger. The performance of the proposed technique is validated in terms of prediction accuracy. Ultimately the analysis proves that the proposed technique is more beneficial for the modelling of heat exchanger.
PAPER REVISED: 2019-05-11
PAPER ACCEPTED: 2019-06-01
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THERMAL SCIENCE YEAR 2020, VOLUME 24, ISSUE Issue 1, PAGES [499 - 503]
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© 2022 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence