Prediction of the Effect of Polymer Membrane Composition in a Dry Air Humidification Process via Neural Network Modeling

Fakhroleslam, M.; Samimi, A.; Mousavi, S.A.; Rezaei, R.

Document Type : Full article

Authors

¹ Chemical and Petroleum Engineering Department, Sharif University of Technology, Tehran, Iran

² Chemical and Petroleum Engineering Department, Sharif University of Technology, Azadi Ave., Tehran, Iran

³ Chemical Engineering Department, Razi University, Kermanshah, Iran

Abstract

Utilization of membrane humidifiers is one of the methods commonly used to humidify reactant gases in polymer electrolyte membrane fuel cells (PEMFC). In this study, polymeric porous membranes with different compositions were prepared to be used in a membrane humidifier module and were employed in a humidification test. Three different neural network models were developed to investigate several parameters, such as casting solution composition, membrane thickness, operating pressure, and flow rate of input dry air which have an impact on relative humidity of the exhausted air after humidification process. The three mentioned models included Feed- Forward Back- Propagation (FBP), Radial Basis Function (RBF), and Feed- Forward Genetic Algorithm (FFGA). The developed models were verified by experimental data. The results showed that the feed- forward neural network models, especially FFGA, were suitable for prediction of the effect of membrane composition and operating conditions on the performance of this type of membrane humidifiers

Keywords

20.1001.1.17355397.2016.13.1.6.9

Main Subjects

References

[1] Mulder, M., Basic principles of membrane technology. 1996: Springer Science & Business Media.

[2] Esato, K. and Eiseman, B., "Experimental evaluation of Gore-Tex membrane oxygenator", J. Thorac. Cardiovasc. Surg., 69 (5), 690 (1975).

[3] Qi, Z. and Cussler, E., "Microporous hollow fibers for gas absorption: I. Mass transfer in the liquid", J. Membrane Sci., 23 (3), 321 (1985).

[4] Zhang, H. Y. Wang, R. Liang, D. T. and Tay, J. H., "Theoretical and experimental studies of membrane wetting in the membrane gas–liquid contacting process for CO 2 absorption", J. Membrane Sci., 308 (1), 162 (2008).

[5] Büchi, F. N. and Srinivasan, S., "Operating proton exchange membrane fuel cells without external humidification of the reactant gases fundamental aspects", J. Electrochem. Soc., 144 (8), 2767 (1997).

[6] Chen, D. Li, W. and Peng, H., "An experimental study and model validation of a membrane humidifier for PEM fuel cell humidification control", J. Power Sources, 180 (1), 461 (2008).

[7] Park, S. and Oh, I. H., "An analytical model of Nafion™ membrane humidifier for proton exchange membrane fuel cells", J. Power Sources, 188 (2), 498 (2009).

[8] Park, S. K. Choe, S. Y, and Choi, S. h., "Dynamic modeling and analysis of a shell-and-tube type gas-to-gas membrane humidifier for PEM fuel cell applications", Int. J. Hydrogen Energy, 33 (9), 2273 (2008).

[9] Kadylak, D. and Mérida, W., "Experimental verification of a membrane humidifier model based on the effectiveness method", J. Power Sources, 195 (10), 3166 (2010)

Iranian Journal of Chemical Engineering(IJChE)

Prediction of the Effect of Polymer Membrane Composition in a Dry Air Humidification Process via Neural Network Modeling

References

References

Volume 13, Issue 1 - Serial Number 1
January 2016
Pages 73-83

Prediction of the Effect of Polymer Membrane Composition in a Dry Air Humidification Process via Neural Network Modeling

References

References

Volume 13, Issue 1 - Serial Number 1January 2016Pages 73-83

Volume 13, Issue 1 - Serial Number 1
January 2016
Pages 73-83