THERMAL SCIENCE

International Scientific Journal

Authors of this Paper

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Alina Bărbulescu

,

Lucica Barbeș

MODELING THE OUTLET TEMPERATURE IN HEAT EXCHANGERS: CASE STUDY

ABSTRACT
This article presents the results of the study of the heat transfer in a heat ex-changer where the working fluid is the crude oil prepared for desalination, and the thermic agent is the re-circulating heavy gasoline fraction. Firstly, the Reynolds numbers have been computed using the temperatures and flow rates of the fluids as input variables. Then, general regression neural network and multi-layer perceptron were used for the outlet temperatures estimation using the inlet temperatures and the Reynolds numbers as input variables. The best models on the training dataset were obtained utilizing a multilayer perceptron with one hidden layer, while the best performance on the validation dataset was obtained using a multilayer perceptron network with two hidden layers.
KEYWORDS
heat transfer, neural networks, Reynolds number, outlet temperature
PAPER SUBMITTED: 2019-09-13
PAPER REVISED: 2019-11-05
PAPER ACCEPTED: 2019-11-07
PUBLISHED ONLINE: 2019-12-22
DOI REFERENCE: https://doi.org/10.2298/TSCI190913449B
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2021, VOLUME 25, ISSUE Issue 1, PAGES [591 - 602]
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Modeling the outlet temperature in heat exchangers: Case study

© 2024 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