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International Journal of Chemical Reactor Engineering

Ed. by de Lasa, Hugo / Xu, Charles Chunbao

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1542-6580
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Experimental Study and Mathematical Modeling of Propane-SCR-NOx Using Group Method of Data Handling and Artificial Neural Network

N. Ghasemian
  • Corresponding author
  • Department of Polymer Science and Engineering, University of Bonab, P.O. Box 55517–61167, Bonab, Iran
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/ H. Nourmoradi
  • Department of Environmental Health Engineering, School of Health, Ilam University of Medical Sciences, Ilam, Iran
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Published Online: 2016-02-16 | DOI: https://doi.org/10.1515/ijcre-2015-0159

Abstract

In this study, the catalytic behavior of protonated clinoptilolite in propane-SCR-NOx was investigated. The experiments were carried out in the temperature range of 200–500 °C as a function of zeolite mesh size 20, 35 and 70 at different weights of zeolite (0.45–1 g) and flow rates (300–600 ml/min) and consequently at various gas hourly space velocities (GHSV). Group method of data handling (GMDH) and artificial neural network (ANN) system were applied for mathematical modeling of NOx conversion to N2 in propane-SCR-NOx. The operating temperature (T), volumetric flow rate (F) and the weight of clinoptilolite zeolite (W) and the conversion of NOx to N2 (X) were considered as the inputs and output, respectively. In order to evaluate the models performance, conversions of NOx obtained from the GMDH and ANN systems were compared with those obtained from the experimental method. It is concluded that the ANN could successively estimate the conversion and the results were in a good agreement with the experimental data.

Keywords: NOx conversion; propane-SCR-NOx; model; GMDH; artificial neural network

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About the article

Published Online: 2016-02-16

Published in Print: 2016-04-01


Citation Information: International Journal of Chemical Reactor Engineering, Volume 14, Issue 2, Pages 559–569, ISSN (Online) 1542-6580, ISSN (Print) 2194-5748, DOI: https://doi.org/10.1515/ijcre-2015-0159.

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