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Modeling heat exchanger using neural networks

Tools to predict the effects caused by frequent changes in the feedstock and in the operating condition in crude preheat train (CPT) in a refinery are essential to maintain optimal operating conditions in the heat exchanger. Currently, no such tools are used in industries. In this paper, an approach...

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Main Authors: T.R., Biyanto, M., Ramasamy, H., Zabiri
Format: Conference or Workshop Item
Published: 2007
Subjects:
TP Chemical technology
Online Access:http://eprints.utp.edu.my/2759/1/modeling_heat_exchanger_using_neural_networks.pdf
http://www.scopus.com/inward/record.url?eid=2-s2.0-57949108485&partnerID=40&md5=93721787b4e81cc982e23cb5f67aa270
http://eprints.utp.edu.my/2759/
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spelling my.utp.eprints.27592017-01-19T08:27:14Z Modeling heat exchanger using neural networks T.R., Biyanto M., Ramasamy H., Zabiri TP Chemical technology Tools to predict the effects caused by frequent changes in the feedstock and in the operating condition in crude preheat train (CPT) in a refinery are essential to maintain optimal operating conditions in the heat exchanger. Currently, no such tools are used in industries. In this paper, an approach based on Nonlinear Auto Regressive with eXogenous input (NARX) type multi layer perceptron neural network model is proposed. This model serves as the prediction tool in order to determine the optimal operating conditions. The neural network model was developed using data collected from CPT in a refinery. In addition to the data on flow rates and temperatures of the streams in the heat exchanger, data on physico-chemical properties and crude blend were also included as input variables to the model. It was observed that the Root Mean Square Error (RMSE) during training and validation phases are less than 0.3°C proving that the modeling approach employed in this research is suitable to capture the complex and nonlinear characteristics of the heat exchanger. ©2007 IEEE. 2007 Conference or Workshop Item PeerReviewed application/pdf http://eprints.utp.edu.my/2759/1/modeling_heat_exchanger_using_neural_networks.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-57949108485&partnerID=40&md5=93721787b4e81cc982e23cb5f67aa270 T.R., Biyanto and M., Ramasamy and H., Zabiri (2007) Modeling heat exchanger using neural networks. In: 2007 International Conference on Intelligent and Advanced Systems, ICIAS 2007, 25 November 2007 through 28 November 2007, Kuala Lumpur. http://eprints.utp.edu.my/2759/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic TP Chemical technology
spellingShingle TP Chemical technology
T.R., Biyanto
M., Ramasamy
H., Zabiri
Modeling heat exchanger using neural networks
description Tools to predict the effects caused by frequent changes in the feedstock and in the operating condition in crude preheat train (CPT) in a refinery are essential to maintain optimal operating conditions in the heat exchanger. Currently, no such tools are used in industries. In this paper, an approach based on Nonlinear Auto Regressive with eXogenous input (NARX) type multi layer perceptron neural network model is proposed. This model serves as the prediction tool in order to determine the optimal operating conditions. The neural network model was developed using data collected from CPT in a refinery. In addition to the data on flow rates and temperatures of the streams in the heat exchanger, data on physico-chemical properties and crude blend were also included as input variables to the model. It was observed that the Root Mean Square Error (RMSE) during training and validation phases are less than 0.3°C proving that the modeling approach employed in this research is suitable to capture the complex and nonlinear characteristics of the heat exchanger. ©2007 IEEE.
format Conference or Workshop Item
author T.R., Biyanto
M., Ramasamy
H., Zabiri
author_facet T.R., Biyanto
M., Ramasamy
H., Zabiri
author_sort T.R., Biyanto
title Modeling heat exchanger using neural networks
title_short Modeling heat exchanger using neural networks
title_full Modeling heat exchanger using neural networks
title_fullStr Modeling heat exchanger using neural networks
title_full_unstemmed Modeling heat exchanger using neural networks
title_sort modeling heat exchanger using neural networks
publishDate 2007
url http://eprints.utp.edu.my/2759/1/modeling_heat_exchanger_using_neural_networks.pdf
http://www.scopus.com/inward/record.url?eid=2-s2.0-57949108485&partnerID=40&md5=93721787b4e81cc982e23cb5f67aa270
http://eprints.utp.edu.my/2759/
_version_ 1738655218701172736
score 13.211869

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