Korean Journal of Chemical Engineering, Vol.32, No.1, 159-167, 2015
Experimental and computational investigation of polyacrylonitrile ultrafiltration membrane for industrial oily wastewater treatment
An experimental study on separation of industrial oil from oily wastewater has been done. A polyacrylonitrile membrane with a molecular weight cut-off (MWCO) of 20 kDa was used and an outlet wastewater of API unit of Tehran refinery was employed. The main purpose of this study was to develop a support vector machine model for permeation flux decline and fouling resistance in a cross-flow hydrophilic polyacrylonitrile membrane during ultrafiltration. The operating conditions which have been applied to develop a support vector machine model were transmembrane pressure (TMP), operating temperature, cross flow velocity (CFV), pH values of oily wastewater, permeation flux decline and fouling resistance. The testing results obtained by the support vector machine models are in very good agreement with experimental data. The calculated squared correlation coefficients for permeation flux decline and fouling resistance were both 0.99. Based on the results, the support vector machine proved to be a reliable accurate
estimation method.
[References]
Cheryan M, Rajagopalan N, J. Membr. Sci. , 151 , 15, 1998
Abbasi M, Salahi A, Mirfendereski M, Mohammadi T, Pak A, Desalination , 252 (1-3), 113, 2010
Srijaroonrat P, Julien E, Aurelle Y, J. Membr. Sci. , 159 (1-2), 11, 1999
Bai H, Wang X, Zhou Y, Zhang L, J. Prog. Nat. Sci. , 250 , 3, 2012
Mohammadi T, Kazemimoghadam M, Saadabadi M, Desalination , 157 (1-3), 369, 2003
Salahi A, Abbasi M, Mohammadi T, Desalination , 251 (1-3), 153, 2010
Yu B, Cong H, Zhao X, J. Prog. Nat. Sci. , 22 , 662, 2012
Cheng C, Uhe J, Yang X, Wu Y, Li D, J. Prog. Nat. Sci. , 22 , 670, 2012
Dave YG, Reddy AVR, Desalination , 282 , 9, 2011
Yang D, Zhang X, Yuan L, Hu J, J. Prog. Nat. Sci. , 19 , 1305, 2009
Xu J, Feng XS, Chen PP, Gao CJ, J. Membr. Sci. , 413 , 62, 2012
Hoek EMV, Allred J, Knoell T, Jeong BH, J. Membr. Sci. , 314 (1-2), 33, 2008
Tu SC, Ravindran V, Pirbazari M, J. Membr. Sci. , 265 (1-2), 29, 2005
Van der Bruggen B, Manttari M, Nystrom M, Sep. Purif. Technol. , 63 (2), 251, 2008
Boerlage SFE, Kennedy MD, Bonne PAC, Galjaard G, Schippers JC, Desalination , 113 (2-3), 231, 1997
Yin N, Chen S, Ouyang Y, Tang L, Yang J, Wang H, J. Prog. Nat. Sci. , 21 , 472, 2011
Ballo S, Liu M, Hou L, Chang J, J. Prog. Nat. Sci. , 19 , 873, 2009
Gunalan S, Sivaraj R, Rajendran V, J. Prog. Nat. Sci. , 22 , 695, 2012
Shokrkar H, Salahi A, Kasiri N, Mohammadi T, Chem. Eng. Res. Des. , 90 (6), 846, 2012
Hwang TM, Oh H, Choung YK, Oh S, Jeon M, Kim JH, Nam SH, Lee S, Desalination , 247 (1-3), 285, 2009
Liu QF, Kim SH, Lee S, Sep. Purif. Technol. , 70 (1), 96, 2009
Madaeni SS, Kurdian AR, Chem. Eng. Res. Des. , 89 (4A), 456, 2011
APHA-American Public Health Association/American Water Works Association/Water Environment Federation, Standard Methods for the Examination of Water and Wastewater, 20th Ed., Washington DC, USA., 2001
Abadi SRH, Sebzari MR, Hemati M, Rekabdar F, Mohammadi T, Desalination , 265 (1-3), 222, 2011
Mohammadi T, Esmaeelifar A, J. Membr. Sci. , 254 (1-2), 129, 2005
Hearst MA, Dumais ST, Osman E, Platt J, Scholkopf B, IEEE Intell. Syst. Appl. , 13 , 18, 1998
Schmidt M, Identifying speaker with support vector networks, In Interface 96 Proceedings, Sydney, 1996
Cristianini N, Taylor JS, An introduction to support vector machine (and other kernel-based learning methods), Cambridge Univ. Press, Cambridge, 2000
Vapnik VN, Statistical learning theory, Wiley, New York, 1998
Pontil M, Verri A, Neural Comput. , 10 , 955, 1998
Eslamimanesh A, Gharagheizi F, Illbeigi M, Mohammadi AH, Fazlali A, Richon D, Fluid Phase Equilib. , 316 , 34, 2012
Balabin RM, Lomakina EI, Phys. Chem. Chem. Phys. , 13 , 11710, 2011
Suykens JAK, Van Gestel T, De Brabanter J, De Moor B, Vandewalle J, Least Squares Support Vector Machines, World Scientific, Singapore, 2002
Suykens JAK, Vandewalle J, Neural Process. Lett. , 9 , 293, 1999
Pelckmans K, Suykens JAK, Van Gestel T, De Brabanter D, Lukas L, Hamers B, De Moor B, Vandewalle J, LS-SVMlab: a Matlab/C Toolbox for Least Squares Support Vector Machines, Internal Report 02-44, ESATSISTA, K.U. Leuven, Belgium, 2002
Vapnik VN, The Nature of Statistical Learning Theory, 2nd Ed. Springer, New York, 1995
Zhao CY, Zhang HX, Zhang XY, Liu MC, Hu ZD, Fan BT, Toxicol. , 217 , 105, 2006
Peng X, Pattern Recog. Lett. , 44 , 2678, 2011
Zanghirati G, Zanni L, Parallel Comput. , 29 , 535, 2003
Terzica J, Nagarajahb CR, Alamgira M, Sens. Actuators , 161 , 278, 2010
Agarwal S, Saradhi VV, Karnick H, Neurocomputing. , 71 , 1230, 2008
Strack R, Kecman V, Strack B, Li Q, Neurocomputing , 59 , 101, 2013
Li DC, Fang YH, Expert. Syst. Appl. , 34 , 2013, 2008
Comak E, Arslan A, Expert. Syst. Appl. , 35 , 564, 2008
Hwang JP, Park S, Kim E, Expert. Syst. Appl. , 38 , 8580, 2011
Salooki MK, Abedini R, Adib H, Koolivand H, Sep. Purif. Technol. , 1 , 82, 2011
Adib H, Haghbakhsh R, Saidi M, Takassi MA, Sharifi F, Koolivand M, Rahimpour MR, Keshtkari S, J. Nat. Gas Sci. Eng. , 10 , 14, 2013
Haghbakhsh R, Adib H, Keshavarz P, Koolivand M, Keshtkari S, Thermochim. Acta , 551 , 124, 2013
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