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MODELING OF OVERALL HEAT TRANSFER COEFFICIENT OF A CONCENTRIC DOUBLE PIPE HEAT EXCHANGER WITH LIMITED EXPERIMENTAL DATA BY USING CURVE FITTING AND ANN COMBINATION

ABSTRACT
The modeling accuracy of artificial neural networks (ANN) was evaluated by using limited heat exchanger data acquired experimentally. The artificial neural networks were used for predicting the overall heat transfer coefficient of a concentric double pipe heat exchanger where oil flowed inside the inner tube while the water flowed in the outer tube. In the cases of parallel and counter flows, the experimental data were collected by testing heat exchanger in wide range of operating conditions. Curve fitting and artificial neural network combination was used for the estimation of the overall heat transfer coefficient to compensate the experimental errors in the data. The curve fitting was used to detect the trend and generate data points between the experimentally collected points. The artificial neural network was trained better from the generated data set. The feed forward type artificial neural network was trained by using the Levenberg-Marquardt algorithm. Two backpropagation network type artificial neural network algorithms were also used, and their performance were compared with the estimation of the Levenberg-Marquardt algorithm. The average estimation error between the predictions and the experimental data were in the range of 1.31e–4 to 4.35e–2%. The study confirmed that curve fitting and artificial neural network combination could be used effectively to estimate the overall heat transfer coefficient of heat exchanger.
KEYWORDS
PAPER SUBMITTED: 2017-12-06
PAPER REVISED: 2018-02-28
PAPER ACCEPTED: 2018-03-12
PUBLISHED ONLINE: 2018-04-28
DOI REFERENCE: https://doi.org/10.2298/TSCI171206111K
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2019, VOLUME 23, ISSUE Issue 6, PAGES [3579 - 3590]
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© 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