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Application of artificial neural networks for estimation of the reaction rate in methanol dehydration / Peyvand Valeh-e-Sheyda in Industrial & engineering chemistry research, Vol. 49 N° 10 (Mai 2010) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 49 N° 10 (Mai 2010) . - pp. 4620–4626 Titre : Application of artificial neural networks for estimation of the reaction rate in methanol dehydration Type de document : texte imprimé Auteurs : Peyvand Valeh-e-Sheyda, Auteur ; Farhooman, Fereydoon, Auteur ; Gholamreza Moradi, Auteur Année de publication : 2010 Article en page(s) : pp. 4620–4626 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Artificial  neural  networks  Methanol Résumé : In this paper, the artificial neural network has been applied to estimate the reaction rate of methanol dehydration in dimethyl ether synthesis. The multilayer feed forward neural network with three inputs and one output has been trained with different algorithms and different numbers of neurons in the hidden layer. Two thirds of all training data are used for training of the network and the rest are used for testing of the generalization of the network. The accuracy of the proposed model was found to agree well with the experimental results over a wide range of experimental conditions. The results clearly depict that the neural network is a powerful tool to estimate the reaction rate and the designed neural network can be used instead of approximate and complex analytical equations. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie9020705 [article] Application of artificial neural networks for estimation of the reaction rate in methanol dehydration [texte imprimé] / Peyvand Valeh-e-Sheyda, Auteur ; Farhooman, Fereydoon, Auteur ; Gholamreza Moradi, Auteur . - 2010 . - pp. 4620–4626. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 49 N° 10 (Mai 2010) . - pp. 4620–4626 Mots-clés : Artificial  neural  networks  Methanol Résumé : In this paper, the artificial neural network has been applied to estimate the reaction rate of methanol dehydration in dimethyl ether synthesis. The multilayer feed forward neural network with three inputs and one output has been trained with different algorithms and different numbers of neurons in the hidden layer. Two thirds of all training data are used for training of the network and the rest are used for testing of the generalization of the network. The accuracy of the proposed model was found to agree well with the experimental results over a wide range of experimental conditions. The results clearly depict that the neural network is a powerful tool to estimate the reaction rate and the designed neural network can be used instead of approximate and complex analytical equations. ISSN : 0888-5885 En ligne : http://pubs.acs.org/doi/abs/10.1021/ie9020705

Effects of feed composition and space velocity on direct synthesis of dimethyl ether from syngas / Gholamreza Moradi in Industrial & engineering chemistry research, Vol. 47 N°20 (Octobre 2008) 

Public ISBD [article]  in Industrial & engineering chemistry research > Vol. 47 N°20 (Octobre 2008) . - P. 7672-7679 Titre : Effects of feed composition and space velocity on direct synthesis of dimethyl ether from syngas Type de document : texte imprimé Auteurs : Gholamreza Moradi, Editeur scientifique ; Javad Ahmadpour, Editeur scientifique ; Mahdi Nazari, Editeur scientifique Année de publication : 2008 Article en page(s) : P. 7672-7679 Note générale : Chemical engineering Langues : Anglais (eng) Mots-clés : Feed  composition  Space  velocity  Bifunctional  catalyst  (CuO/ZnO/Al2O3+  H-ZSM-5) Résumé : Full factorial experimental design method was applied for investigation of the effects of different space velocity (SV) (500−1500 mLn/(g-cat.h)) and H2/CO molar feed ratio (1−2) on CO conversion and/or DME selectivity as the response variables over a physically prepared bifunctional catalyst (CuO/ZnO/Al2O3+ H-ZSM-5) for liquid phase direct DME synthesis from synthesis gas. The results showed that feed composition is the more effective factor on the response and the interaction of the SV and H2/CO only slightly influenced the response. The factor levels that can maximize the SDME are SV of 1500 mLn/(g-cat.h) and H2/CO of 1.5 at 240 °C and 35 bar. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie800888z [article] Effects of feed composition and space velocity on direct synthesis of dimethyl ether from syngas [texte imprimé] / Gholamreza Moradi, Editeur scientifique ; Javad Ahmadpour, Editeur scientifique ; Mahdi Nazari, Editeur scientifique . - 2008 . - P. 7672-7679. Chemical engineering Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 47 N°20 (Octobre 2008) . - P. 7672-7679 Mots-clés : Feed  composition  Space  velocity  Bifunctional  catalyst  (CuO/ZnO/Al2O3+  H-ZSM-5) Résumé : Full factorial experimental design method was applied for investigation of the effects of different space velocity (SV) (500−1500 mLn/(g-cat.h)) and H2/CO molar feed ratio (1−2) on CO conversion and/or DME selectivity as the response variables over a physically prepared bifunctional catalyst (CuO/ZnO/Al2O3+ H-ZSM-5) for liquid phase direct DME synthesis from synthesis gas. The results showed that feed composition is the more effective factor on the response and the interaction of the SV and H2/CO only slightly influenced the response. The factor levels that can maximize the SDME are SV of 1500 mLn/(g-cat.h) and H2/CO of 1.5 at 240 °C and 35 bar. En ligne : http://pubs.acs.org/doi/abs/10.1021/ie800888z