Hostname: page-component-cd9895bd7-gxg78 Total loading time: 0 Render date: 2024-12-26T20:58:57.922Z Has data issue: false hasContentIssue false
  • English
  • Français

Hybrid Particle Swarm-Ant Colony Algorithm to Describe the Phase Equilibrium of Systems Containing Supercritical Fluids with Ionic Liquids

Published online by Cambridge University Press:  03 June 2015

Juan A. Lazzús
Juan A. Lazzús*
Affiliation:
Departamento de Física, Universidad de La Serena, Casilla 554, La Serena, Chile
*
*Corresponding author.Email:[email protected]
Get access

Abstract

Based on biologically inspired algorithms, a thermodynamic model to describe the vapor-liquid equilibrium of binary complex mixtures containing supercritical fluids and ionic liquids, is presented. The Peng-Robinson equation of state with the Wong-Sandler mixing rules are used to evaluate the fugacity coefficient on the systems. Then, a hybrid particle swarm-ant colony optimization was used to minimize the difference between calculated and experimental bubble pressure, and calculate the binary interaction parameters for the excess Gibbs free energy of all systems used. Simulations are carried out in nine systems with imidazolium-based ionic liquids. The results show that the bubble pressures were correlated with low deviations between experimental and calculated values. These deviations show that the proposed hybrid algorithm is the preferable method to describe the phase equilibrium of these complex mixtures, and can be used for other similar systems.

Keywords

80M5092-0882D1582B2651.30.+i64.75.Cd02.60.PnParticle swarm optimizationant colony optimizationvapor-liquid equilibriumionic liquidssupercritical fluidsPeng-Robinson equation of state
Type
Research Article
Information
Communications in Computational Physics , Volume 14 , Issue 1 , July 2013 , pp. 107 - 125
Copyright
Copyright © Global Science Press Limited 2013

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

[1]Lazzuús, J. A., Peérez Ponce, A. A. and Palma Chilla, L. O., Fluid Phase Equilib. 317, 132 (2012).Google Scholar
[2]Blanchard, L. A., Hancu, D., Beckman, E. J. and Brennecke, J. F., Nature 399, 28 (1999).Google Scholar
[3]Hong, G., Jacquemin, J., Deetlefs, M., Hardacre, C., Husson, P. and Costa Gomes, M. F., Fluid Phase Equilib. 257, 27 (2007).Google Scholar
[4]Lazzuús, J. A., Eng, J.Thermophys. 18, 306 (2009).Google Scholar
[5]Lazzuús, J. A., Comput. Math. Appl. 60, 2260 (2010).Google Scholar
[6]Lazzuús, J. A. and Palma Chilla, L. O., Eng, J.Thermophys. 20, 101 (2011).Google Scholar
[7]Kennedy, J., Eberhart, R. C. and Shi, Y., Swarm Intelligence (Morgan Kaufman, San Francisco, 2001).Google Scholar
[8]Dorigo, M. and Gambardella, L. M., Biosystems 43, 73 (1997).Google Scholar
[9]Walas, S. M., Phase Equilibria in Chemical Engineering (Butterworth-Heinemenn, Boston, 1985).Google Scholar
[10]Orbey, H. and Sandler, S. I., Modeling Vapor-Liquid Equilibria. Cubic Equations of State and Their Mixing Rules (Cambridge University Press, USA, 1998).Google Scholar
[11]Lazzuús, J. A. and Marín, J., Eng, J.Thermophys. 19, 170 (2010).Google Scholar
[12]Peng, D. Y. and Robinson, D. B., Ind. Eng. Chem. Fund. 15, 59 (1976).Google Scholar
[13]Wong, D. S. H. and Sandler, S. I., AIChE J. 38, 671 (1992).Google Scholar
[14]Jiang, Y., Hu, T., Huang, C. C. and Wu, X., Appl. Math. Comput. 193, 231 (2007).Google Scholar
[15]Da, T. and Xiurun, G., Neurocomputing 63, 527 (2005).Google Scholar
[16]Shi, Y. and Eberhart, R., A modified particle swarm optimizer IEEE International Conference on Evolutionary Computation (IEEE Press, Piscataway, 1998) pp. 69–73.Google Scholar
[17]Kuran, M. S., Ozceylan, E., Gunduz, M. and Paksoy, T., Energy Convers. Manage. 53, 75 (2012).Google Scholar
[18]Niknam, T. and Amiri, B., Appl. Soft Comput. 10, 183 (2010).Google Scholar
[19]Muller, R. J., Monekosso, D., Barman, S. and Remagnino, P., Exp. Syst. Appl. 36, 9608 (2009).Google Scholar
[20]Shelokar, P. S., Siarry, P., Jayaraman, V. K. and Kulkarni, B. D., Appl. Math. Comput. 188, 129 (2007).Google Scholar
[21]Kaveh, A. and S. Talatahari, , J., AsianCivil Eng. 10, 611 (2009).Google Scholar
[22]Marinakis, Y., Marinaki, M., Doumpos, M. and Zopounidis, C., Exp. Syst. Appl. 36, 10604 (2009).Google Scholar
[23]Valderrama, J. O. and Robles, P. A., Ind. Eng. Chem. Res. 46, 1338 (2007).Google Scholar
[24]Valderrama, J. O., Sanga, W. W. and Lazzuús, J. A., Ind. Eng. Chem. Res. 47, 1318 (2008).Google Scholar
[25]Daubert, T. E., Danner, R. P., Sibul, H. M. and Stebbins, C. C., Physical and Thermodynamic Properties of Pure Chemicals. Data Compilation (Taylor & Francis, London, 1996).Google Scholar
[26]Carvalho, P. J., Alvarez, V. H., Machado, J. J. B., Pauly, J., Daridon, J. L., Marrucho, I. M., Aznar, M. and Coutinho, J. A. P., Supercrit, J.Fluids 48, 99 (2009).Google Scholar
[27]Aki, S. N. V. K., Mellein, B. R., Saurer, E. M. and Brennecke, J. F., J. Phys. Chem. B 108, 20355 (2004).Google Scholar
[28]Blanchard, L. A., Gu, Z. and Brennecke, J. F., J. Phys. Chem. B 105, 2437 (2001).Google Scholar
[29]Coutsikos, P., Magoulas, K. and Kontogeorgis, G. M., Supercrit, J.Fluids 25, 197 (2003).Google Scholar
[30]Trebble, M. A. and Bishnoi, P. R., Fluid Phase Equilib. 40, 1 (1988).Google Scholar
[31]Holland, J., Adaptation in Natural and Artificial Systems (University of Michigan Press, USA, 1975).Google Scholar
[32]Reilly, M., Computer Programs for Chemical Engineering Education (Sterling Swift, Texas, 1972).Google Scholar