{"title":"Studies on the Applicability of Artificial Neural Network (ANN) in Prediction of Thermodynamic Behavior of Sodium Chloride Aqueous System Containing a Non-Electrolytes","authors":"Dariush Jafari, S. Mostafa Nowee","volume":97,"journal":"International Journal of Computer and Information Engineering","pagesStart":110,"pagesEnd":114,"ISSN":"1307-6892","URL":"https:\/\/publications.waset.org\/pdf\/10000395","abstract":"
In this study a ternary system containing sodium
\r\nchloride as solute, water as primary solvent and ethanol as the
\r\nantisolvent was considered to investigate the application of artificial
\r\nneural network (ANN) in prediction of sodium solubility in the
\r\nmixture of water as the solvent and ethanol as the antisolvent. The
\r\nsystem was previously studied using by Extended UNIQUAC model
\r\nby the authors of this study. The comparison between the results of
\r\nthe two models shows an excellent agreement between them
\r\n(R2=0.99), and also approves the capability of ANN to predict the
\r\nthermodynamic behavior of ternary electrolyte systems which are
\r\ndifficult to model.<\/p>\r\n","references":"[1] S.O.P. Pinho, and E.N.A. Macedo, \"Solubility of NaCl, NaBr, and KCl\r\nin Water, Methanol, Ethanol, and Their Mixed Solvents\", J. Chem. Eng.\r\nData, vol. 50, no. 1, pp. 29-32, 2004.\r\n[2] O. Chiavone-Filho and P. Rasmussen, \"Solubilities of salts in mixed\r\nsolvents\", J. Chem. Eng. Data, vol. 38, pp. 367-369,1993.\r\n[3] J.W. Lorimer, \"Thermodynamics of solubility in mixed solvent\r\nsystems\", Pure Appl. Chem., vol. 65, pp. 183-191, 1993.\r\n[4] K. Thomsen, M. C. Iliuta, and P. Rasmussen, \"Extended UNIQUAC\r\nmodel for correlation and prediction of vapor-liquid-liquid-solid\r\nequilibria in aqueous salt systems containing non-electrolytes. Part B.\r\nAlcohol (ethanol, propanols, butanols)-water-salt systems\", Chem. Eng.\r\nSci., vol. 59, no. 17, pp. 3631-3647, 2004.\r\n[5] K. Thomsen and P. Rasmussen, \"Modeling of vapour-liquid-solid\r\nequilibrium in gas-aqueous electrolyte systems\", Chem. Eng. Sci., vol.\r\n54, pp. 1787-1802, 1999.\r\n[6] K. Thomsen, \"Modeling electrolyte solutions with the extended\r\nuniversal quasichemical (UNIQUAC) model\", Pure Appl. Chem.,.\r\nvol.77, no. 3, pp. 531-542, 2005.\r\n[7] D. Jafari, S. M. Nowee, and S H. Noie, \"The prediction of\r\nThermodynamic-Kinetic behavior of anti solvent crystallization from\r\nSodium Chloride aqueous systems containing Non-electrolytes\"\r\nInternational Journal of Applied Science and Engineering Research, vol.\r\n1, no. 2, pp. 312-326, 2012.\r\n[8] G. S. Shephard, S. Stockenstroma, D. Villiers, W.J. Engelbrecht, and\r\nG.F.S. Wessels, \"Degradation of microcystin toxins in a falling film\r\nphotocatalytic reactor with immobilized titanium dioxide catalyst\",\r\nWater Res., vol. 36, no. 1, pp. 140-146, 2002.\r\n[9] A.R. Soleymani, J. Saiena, and H. Bayat, \"Artificial neural networks\r\ndeveloped for prediction of dye decolorization efficiency with\r\nUV\/K2S2O8 process\", Chem. Eng. J., vol. 170, no. 1, pp. 29-35, 2011.\r\n[10] A. Aleboyeh, M.B. Kasiri, M.E. Olya, and H. Aleboyeh, \"Prediction of\r\nazo dye decolorization by UV\/H2O2 using artificial neural networks\",\r\nDyes. Pigments., vol.77, no. 2, pp. 288-294, 2008.\r\n[11] M. Chakraborty, C. Bhattacharya, and S. Dutta, \"Studies on the\r\napplicability of artificial neural network (ANN) in emulsion liquid\r\nmembranes\", J. Membrane. Sci., vol. 220, no. 1, pp. 155-164, 2003.\r\n[12] S. Aminossadati, A. Kargar, and B. Ghasemi, \"Adaptive network-based\r\nfuzzy inference system analysis of mixed convection in a two-sided liddriven\r\ncavity filled with a nanofluid\", Int. J. Therm. Sci. vol. 52, pp.\r\n102-111, 2012.\r\n[13] V.K. Devabhaktuni, M. Yagoub, Y. Fang, J. Xu, and Q. Zhang, \"Neural\r\nnetworks for microwave modeling: Model development issues and\r\nnonlinear modeling techniques\", J. RF Microwave Comput. Aided Eng.,\r\nvol. 11, no. 1, pp. 4-21, 2001.\r\n[14] R. Abedini, M. Esfandyari, A. Nezhadmoghadam, and B. Rahmanian,\r\n\"The prediction of undersaturated crude oil viscosity: An artificial neural\r\nnetwork and fuzzy model approach\", Pet. Sci. Technol., vol. 30, no.\r\n19, pp. 2008-2021, 2012.\r\n[15] K. Thomsen, P. Rasmussen, and R. Gani, \"Correlation and prediction of\r\nthermal properties and phase behaviour for a class of aqueous electrolyte\r\nsystems\", Chem. Eng. Sci., vol. 51, 99. 3675-3683, 1996. ","publisher":"World Academy of Science, Engineering and Technology","index":"Open Science Index 97, 2015"}