International Scientific Journal
MODELING THE OUTLET TEMPERATURE IN HEAT EXCHANGERS: CASE STUDY
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.
PAPER SUBMITTED: 2019-09-13
PAPER REVISED: 2019-11-05
PAPER ACCEPTED: 2019-11-07
PUBLISHED ONLINE: 2019-12-22
, VOLUME 25
, ISSUE Issue 1
, PAGES [591 - 602]
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