Hybrid neural network for prediction of CO2 solubility in monoethanolamine and diethanolamine solutions

Hussain, Mohd Azlan and Aroua, Mohamed Kheireddine and Yin, Chun Yang and Rahman, Ramzalina Abd and Ramli, Noor Asriah (2010) Hybrid neural network for prediction of CO2 solubility in monoethanolamine and diethanolamine solutions. Korean Journal of Chemical Engineering, 27 (6). pp. 1864-1867. ISSN 0256-1115, DOI https://doi.org/10.1007/s11814-010-0270-z.

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Official URL: https://doi.org/10.1007/s11814-010-0270-z


The solubility of CO 2 in single monoethanolamine (MEA) and diethanolamine (DEA) solutions was predicted by a model developed based on the Kent-Eisenberg model in combination with a neural network. The combination forms a hybrid neural network (HNN) model. Activation functions used in this work were purelin, logsig and tansig. After training, testing and validation utilizing different numbers of hidden nodes, it was found that a neural network with a 3-15-1 configuration provided the best model to predict the deviation value of the loading input. The accuracy of data predicted by the HNN model was determined over a wide range of temperatures (0 to 120 °C), equilibrium CO 2 partial pressures (0.01 to 6,895 kPa) and solution concentrations (0.5 to 5.0 M). The HNN model could be used to accurately predict CO 2 solubility in alkanolamine solutions since the predicted CO 2 loading values from the model were in good agreement with experimental data.

Item Type: Article
Additional Information: Cited By (since 1996): 2 Export Date: 5 March 2013 Source: Scopus Language of Original Document: English Correspondence Address: Aroua, M. K.; Department of Chemical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia; email: mkaroua@um.edu.my References: Kohl, A.L., Nielsen, R.B., (1997) Gas Purification, , 5 th Ed., Gulf Publishing, Houston, Texas; Benamor, A., Aroua, M.K., (2007) Korean J. Chem. Eng, 24, p. 16; Benamor, A., Aroua, M.K., (2005) Fluid Phase Equilibria, 231, p. 150; Chen, C.C., Britt, H.I., Boston, J.F., Evans, L.B., (1982) AIChE J, 28, p. 588; Deshmukh, R.D., Mather, A.E., (1981) Chem. Eng. Sci, 36, p. 355; Kent, R.L., Eisenberg, B., (1976) Hydrocarbon Process, 55, p. 87; Hussain, M.A., Rahman, M.S., Ng, C.W., (2002) J. Food Eng, 51, p. 239; Danckwerts, P.V., McNeil, K.M., (1967) Trans. Inst. Chem. Eng, 45, p. 32; Lee, J.I., Otto, F.D., Mather, A.E., (1972) J. Chem. Eng. Data, 17, p. 465; Park, J.Y., Yoon, S.J., Lee, H., Yoon, J.H., Shim, J.G., Lee, J.K., Min, B.Y., Kang, M.C., (2002) Fluid Phase Equilibria, 202, p. 359; Daneshvar, N., Zaafarani-Moattar, M.T., Abedinzadegan-Abdi, M., Aber, S., (2004) Sep. Purif. Technol, 37, p. 135; Austgen, D.M., Rochelle, G.T., Chen, C.C., (1991) Ind. Eng. Chem. Res, 30, p. 543; Shen, K.P., Li, M.H., (1992) J. Chem. Eng. Data, 37, p. 96; Jou, F.Y., Mather, A.E., Otto, F.D., (1995) Can. J. Chem. Eng, 73, p. 140; Park, S.H., Lee, K.B., Hyun, J.C., Kim, S.H., (2002) Ind. Eng. Chem. Res, 41, p. 1658; Perrin, D.D., (1965) Dissociation Constants of Organic Bases In Aqueous Solution, , Butterworths, London; Edwards, T.J., Maurer, G., Newman, J., Prausnitz, J.M., (1978) AIChE J, 24, p. 966
Uncontrolled Keywords: CO 2; Diethanolamine; Hybrid neural network; Kent-eisenberg model; Monoethanolamine; Solubility
Subjects: T Technology > TP Chemical technology
Divisions: Faculty of Engineering
Depositing User: Mr Jenal S
Date Deposited: 10 Jul 2013 02:25
Last Modified: 11 Nov 2019 02:04
URI: http://eprints.um.edu.my/id/eprint/7028

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