Estimation of thermal conductivity of ionic liquids using a perceptron neural network / Ali Zeinolabedini Hezave in Industrial & engineering chemistry research, Vol. 51 N° 29 (Juillet 2012)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 51 N° 29 (Juillet 2012) . - pp. 9886-9893 Titre : Estimation of thermal conductivity of ionic liquids using a perceptron neural network Type de document : texte imprimé Auteurs : Ali Zeinolabedini Hezave, Auteur ; Sona Raeissi, Auteur ; Mostafa Lashkarbolooki, Auteur Année de publication : 2012 Article en page(s) : pp. 9886-9893 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Neural network Ionic liquid Thermal conductivity Résumé : On the basis of an artificial neural network (ANN), a model is proposed to predict the thermal conductivity of pure ionic liquids. A total of 209 data points from 21 different ionic liquids was used to train and test the proposed network. The optimum number of hidden layers was determined to be 1, with 13 neurons in the hidden layer and logarithmic―sigmoid and purelin functions as the transfer functions in the hidden and output layers, respectively. The results obtained reveal that the proposed network is able to correlate and predict the thermal conductivity of all of the pure ionic liquids with an overall absolute mean relative deviation percent (MARD %) of 0.5% and mean square error (MSE) of 1.2 × 10―6 The optimized network was also compared with literature correlations and a predictive group contribution method. The results indicate the rather good accuracy of the proposed neural network compared to the previously proposed literature methods. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26184967 [article] Estimation of thermal conductivity of ionic liquids using a perceptron neural network [texte imprimé] / Ali Zeinolabedini Hezave, Auteur ; Sona Raeissi, Auteur ; Mostafa Lashkarbolooki, Auteur . - 2012 . - pp. 9886-9893. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 29 (Juillet 2012) . - pp. 9886-9893 Mots-clés : Neural network Ionic liquid Thermal conductivity Résumé : On the basis of an artificial neural network (ANN), a model is proposed to predict the thermal conductivity of pure ionic liquids. A total of 209 data points from 21 different ionic liquids was used to train and test the proposed network. The optimum number of hidden layers was determined to be 1, with 13 neurons in the hidden layer and logarithmic―sigmoid and purelin functions as the transfer functions in the hidden and output layers, respectively. The results obtained reveal that the proposed network is able to correlate and predict the thermal conductivity of all of the pure ionic liquids with an overall absolute mean relative deviation percent (MARD %) of 0.5% and mean square error (MSE) of 1.2 × 10―6 The optimized network was also compared with literature correlations and a predictive group contribution method. The results indicate the rather good accuracy of the proposed neural network compared to the previously proposed literature methods. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26184967

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité
aucun exemplaire

Liquid–Liquid Phase Equilibria of Systems of Palm and Soya Biodiesels / Masoume Rostami in Industrial & engineering chemistry research, Vol. 51 N° 24 (Juin 2012)  

Public ISBD [article]  inIndustrial & engineering chemistry research > Vol. 51 N° 24 (Juin 2012) . - pp. 8302–8307 Titre : Liquid–Liquid Phase Equilibria of Systems of Palm and Soya Biodiesels : Experimental and Modeling Type de document : texte imprimé Auteurs : Masoume Rostami, Auteur ; Sona Raeissi, Auteur ; Maziyar Mahmoudi, Auteur Année de publication : 2012 Article en page(s) : pp. 8302–8307 Note générale : Industrial chemistry Langues : Anglais (eng) Mots-clés : Modeling Phase equilibrium Liquid liquid Résumé : Liquid–liquid phase equilibria of two systems of concern in the biodiesel production process are determined experimentally. The first system is the binary mixture of water + biodiesel within a temperature range of 297.2 to 333.2 K, in order to determine water solubilities in two biodiesels prepared from palm and soya oil. The experimental results showed that water solubilities were limited to values below 0.05 mol % and that the solubility increased with increasing temperature and biodiesel unsaturation. Next, the phase diagrams of ternary mixtures of glycerol + methanol + mentioned biodiesels were determined at three temperatures (293.2, 303.2, and 313.2 K). The reliability of the experimental data of tie lines was ascertained using the Othmer-Tobias relation. The UNIQUAC model was then used to model both the binary and ternary experimental data. Results showed the suitability of this model in correlating the phase behavior of such systems. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26029665 [article] Liquid–Liquid Phase Equilibria of Systems of Palm and Soya Biodiesels : Experimental and Modeling [texte imprimé] / Masoume Rostami, Auteur ; Sona Raeissi, Auteur ; Maziyar Mahmoudi, Auteur . - 2012 . - pp. 8302–8307. Industrial chemistry Langues : Anglais (eng) in Industrial & engineering chemistry research > Vol. 51 N° 24 (Juin 2012) . - pp. 8302–8307 Mots-clés : Modeling Phase equilibrium Liquid liquid Résumé : Liquid–liquid phase equilibria of two systems of concern in the biodiesel production process are determined experimentally. The first system is the binary mixture of water + biodiesel within a temperature range of 297.2 to 333.2 K, in order to determine water solubilities in two biodiesels prepared from palm and soya oil. The experimental results showed that water solubilities were limited to values below 0.05 mol % and that the solubility increased with increasing temperature and biodiesel unsaturation. Next, the phase diagrams of ternary mixtures of glycerol + methanol + mentioned biodiesels were determined at three temperatures (293.2, 303.2, and 313.2 K). The reliability of the experimental data of tie lines was ascertained using the Othmer-Tobias relation. The UNIQUAC model was then used to model both the binary and ternary experimental data. Results showed the suitability of this model in correlating the phase behavior of such systems. ISSN : 0888-5885 En ligne : http://cat.inist.fr/?aModele=afficheN&cpsidt=26029665

Exemplaires

Code-barres	Cote	Support	Localisation	Section	Disponibilité
aucun exemplaire