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Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach

Modelling polymerization processes involves considerable uncertainties due to the intricate polymerization reaction mechanism involved. The complex reaction kinetics results in highly nonlinear process dynamics. Available conventional models are limited in applicability and cannot describe accuratel...

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Main Authors:	Hosen, M.A., Hussain, Mohd Azlan, Mjalli, F.S.
Format:	Article
Published:	Wiley 2011
Subjects:	TA Engineering (General). Civil engineering (General) TP Chemical technology
Online Access:	http://eprints.um.edu.my/7016/ https://doi.org/10.1002/Apj.435
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spelling	my.um.eprints.70162021-02-10T02:26:43Z http://eprints.um.edu.my/7016/ Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach Hosen, M.A. Hussain, Mohd Azlan Mjalli, F.S. TA Engineering (General). Civil engineering (General) TP Chemical technology Modelling polymerization processes involves considerable uncertainties due to the intricate polymerization reaction mechanism involved. The complex reaction kinetics results in highly nonlinear process dynamics. Available conventional models are limited in applicability and cannot describe accurately the actual physico-chemical characteristics of the reactor dynamics. The usual practice for operating polymerization reactors is to optimize the reactor temperature profile because the end use properties of the product polymer depend highly on temperature. However, to obtain accurate models in order to optimize the temperature profile, the kinetic parameters (i.e. frequency factors and activation energies) for a specific reactor must be determined accurately. Kinetic parameters vary considerably in batch reactors because of its high sensitivity to other reactor design and operational variables such as agitator geometry and speed, gel effects, heating systems, etc. In this work, the kinetic parameters were estimated for a styrene-free radical polymerization conducted in an experimental batch reactor system using a nonlinear least squares optimization algorithm. The estimated kinetic parameters were correlated with respect to reactor operating variables including initial reactor temperature (T o), initial initiator concentration (I o) and heat duty (Q) using artificial neural network (ANN) techniques. The ANN kinetic model was then utilized in combination with the conventional mechanistic model. The experimental validation of the model revealed that the new model has high prediction capabilities compared withother reported models. Wiley 2011 Article PeerReviewed Hosen, M.A. and Hussain, Mohd Azlan and Mjalli, F.S. (2011) Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach. Asia-Pacific Journal of Chemical Engineering, 6 (2). pp. 274-287. ISSN 1932-2135 https://doi.org/10.1002/Apj.435 doi:10.1002/Apj.435
institution	Universiti Malaya
building	UM Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaya
content_source	UM Research Repository
url_provider	http://eprints.um.edu.my/
topic	TA Engineering (General). Civil engineering (General) TP Chemical technology
spellingShingle	TA Engineering (General). Civil engineering (General) TP Chemical technology Hosen, M.A. Hussain, Mohd Azlan Mjalli, F.S. Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach
description	Modelling polymerization processes involves considerable uncertainties due to the intricate polymerization reaction mechanism involved. The complex reaction kinetics results in highly nonlinear process dynamics. Available conventional models are limited in applicability and cannot describe accurately the actual physico-chemical characteristics of the reactor dynamics. The usual practice for operating polymerization reactors is to optimize the reactor temperature profile because the end use properties of the product polymer depend highly on temperature. However, to obtain accurate models in order to optimize the temperature profile, the kinetic parameters (i.e. frequency factors and activation energies) for a specific reactor must be determined accurately. Kinetic parameters vary considerably in batch reactors because of its high sensitivity to other reactor design and operational variables such as agitator geometry and speed, gel effects, heating systems, etc. In this work, the kinetic parameters were estimated for a styrene-free radical polymerization conducted in an experimental batch reactor system using a nonlinear least squares optimization algorithm. The estimated kinetic parameters were correlated with respect to reactor operating variables including initial reactor temperature (T o), initial initiator concentration (I o) and heat duty (Q) using artificial neural network (ANN) techniques. The ANN kinetic model was then utilized in combination with the conventional mechanistic model. The experimental validation of the model revealed that the new model has high prediction capabilities compared withother reported models.
format	Article
author	Hosen, M.A. Hussain, Mohd Azlan Mjalli, F.S.
author_facet	Hosen, M.A. Hussain, Mohd Azlan Mjalli, F.S.
author_sort	Hosen, M.A.
title	Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach
title_short	Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach
title_full	Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach
title_fullStr	Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach
title_full_unstemmed	Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach
title_sort	hybrid modelling and kinetic estimation for polystyrene batch reactor using artificial neutral network (ann) approach
publisher	Wiley
publishDate	2011
url	http://eprints.um.edu.my/7016/ https://doi.org/10.1002/Apj.435
_version_	1691733416869888000
score	13.211869

Hybrid modelling and kinetic estimation for polystyrene batch reactor using Artificial Neutral Network (ANN) approach

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