CALCULATION OF THE BINARY INTERACTION AND NONRANDOMNESS PARAMETERS OF NRTL, NRTL1, AND NRTL2 MODELS USING GENETIC ALGORITHM FOR TERNARY IONIC LIQUID SYSTEMS

Gholamreza Vakili-Nezhaad, Mostafa Vatani, Morteza Asghari

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

One of the most important applications of thermodynamics is the accurate prediction of fluid phase equilibria problems related to real chemical engineering processes. Various equations of state as well as activity coefficient models have been developed for such calculations with many interaction, size, and randomness parameters, which should be optimized based on powerful and effective computational methods. Leading to globally optimal values, genetic algorithm (GA) as a powerful and effective tool can be used for prediction of the interaction parameters of thermodynamic models in complex liquid-liquid equilibrium (LLE) systems. It requires only lower and upper bounds for the interaction parameters and the necessary initial guesses are produced automatically. In the present work, based on the GA method, a global optimization procedure is introduced for calculation of the binary interaction and nonrandomness parameters of NRTL, NRTL1, and NRTL2 activity coefficient models for 20 ternary aromatic extraction systems containing 16 different ionic liquids at various temperatures. The values of the parameters along with the root-mean-square deviations (rmsd) are reported. The results, in terms of rmsd for NRTL, NRTL1, and NRTL2 models, are very satisfactory, with global values of 0.0031, 0.0020, and 0.0053 for 187 tie-lines respectively. The obtained rmsd values for the NRTL model using the GA method are better than those reported in the literature. The rmsd results for the three studied models show that NRTL1 can handle the LLE calculations with more accuracy than the original NRTL and NRTL2 activity coefficient models.

Original languageEnglish
Pages (from-to)1102-1120
Number of pages19
JournalChemical Engineering Communications
Volume200
Issue number8
DOIs
Publication statusPublished - Aug 2013

Fingerprint

Ionic Liquids
Ionic liquids
Genetic algorithms
Activity coefficients
Liquids
Thermodynamics
Chemical engineering
Global optimization
Computational methods
Equations of state
Phase equilibria
Fluids

Keywords

  • Genetic algorithm
  • Ionic liquid
  • NRTL
  • NRTL1
  • NRTL2
  • Parameter estimation

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Chemistry(all)

Cite this

@article{243dc90a6d2b4e258ef4bd1e05d08b17,
title = "CALCULATION OF THE BINARY INTERACTION AND NONRANDOMNESS PARAMETERS OF NRTL, NRTL1, AND NRTL2 MODELS USING GENETIC ALGORITHM FOR TERNARY IONIC LIQUID SYSTEMS",
abstract = "One of the most important applications of thermodynamics is the accurate prediction of fluid phase equilibria problems related to real chemical engineering processes. Various equations of state as well as activity coefficient models have been developed for such calculations with many interaction, size, and randomness parameters, which should be optimized based on powerful and effective computational methods. Leading to globally optimal values, genetic algorithm (GA) as a powerful and effective tool can be used for prediction of the interaction parameters of thermodynamic models in complex liquid-liquid equilibrium (LLE) systems. It requires only lower and upper bounds for the interaction parameters and the necessary initial guesses are produced automatically. In the present work, based on the GA method, a global optimization procedure is introduced for calculation of the binary interaction and nonrandomness parameters of NRTL, NRTL1, and NRTL2 activity coefficient models for 20 ternary aromatic extraction systems containing 16 different ionic liquids at various temperatures. The values of the parameters along with the root-mean-square deviations (rmsd) are reported. The results, in terms of rmsd for NRTL, NRTL1, and NRTL2 models, are very satisfactory, with global values of 0.0031, 0.0020, and 0.0053 for 187 tie-lines respectively. The obtained rmsd values for the NRTL model using the GA method are better than those reported in the literature. The rmsd results for the three studied models show that NRTL1 can handle the LLE calculations with more accuracy than the original NRTL and NRTL2 activity coefficient models.",
keywords = "Genetic algorithm, Ionic liquid, NRTL, NRTL1, NRTL2, Parameter estimation",
author = "Gholamreza Vakili-Nezhaad and Mostafa Vatani and Morteza Asghari",
year = "2013",
month = "8",
doi = "10.1080/00986445.2012.740533",
language = "English",
volume = "200",
pages = "1102--1120",
journal = "Chemical Engineering Communications",
issn = "0098-6445",
publisher = "Taylor and Francis Ltd.",
number = "8",

}

TY - JOUR

T1 - CALCULATION OF THE BINARY INTERACTION AND NONRANDOMNESS PARAMETERS OF NRTL, NRTL1, AND NRTL2 MODELS USING GENETIC ALGORITHM FOR TERNARY IONIC LIQUID SYSTEMS

AU - Vakili-Nezhaad, Gholamreza

AU - Vatani, Mostafa

AU - Asghari, Morteza

PY - 2013/8

Y1 - 2013/8

N2 - One of the most important applications of thermodynamics is the accurate prediction of fluid phase equilibria problems related to real chemical engineering processes. Various equations of state as well as activity coefficient models have been developed for such calculations with many interaction, size, and randomness parameters, which should be optimized based on powerful and effective computational methods. Leading to globally optimal values, genetic algorithm (GA) as a powerful and effective tool can be used for prediction of the interaction parameters of thermodynamic models in complex liquid-liquid equilibrium (LLE) systems. It requires only lower and upper bounds for the interaction parameters and the necessary initial guesses are produced automatically. In the present work, based on the GA method, a global optimization procedure is introduced for calculation of the binary interaction and nonrandomness parameters of NRTL, NRTL1, and NRTL2 activity coefficient models for 20 ternary aromatic extraction systems containing 16 different ionic liquids at various temperatures. The values of the parameters along with the root-mean-square deviations (rmsd) are reported. The results, in terms of rmsd for NRTL, NRTL1, and NRTL2 models, are very satisfactory, with global values of 0.0031, 0.0020, and 0.0053 for 187 tie-lines respectively. The obtained rmsd values for the NRTL model using the GA method are better than those reported in the literature. The rmsd results for the three studied models show that NRTL1 can handle the LLE calculations with more accuracy than the original NRTL and NRTL2 activity coefficient models.

AB - One of the most important applications of thermodynamics is the accurate prediction of fluid phase equilibria problems related to real chemical engineering processes. Various equations of state as well as activity coefficient models have been developed for such calculations with many interaction, size, and randomness parameters, which should be optimized based on powerful and effective computational methods. Leading to globally optimal values, genetic algorithm (GA) as a powerful and effective tool can be used for prediction of the interaction parameters of thermodynamic models in complex liquid-liquid equilibrium (LLE) systems. It requires only lower and upper bounds for the interaction parameters and the necessary initial guesses are produced automatically. In the present work, based on the GA method, a global optimization procedure is introduced for calculation of the binary interaction and nonrandomness parameters of NRTL, NRTL1, and NRTL2 activity coefficient models for 20 ternary aromatic extraction systems containing 16 different ionic liquids at various temperatures. The values of the parameters along with the root-mean-square deviations (rmsd) are reported. The results, in terms of rmsd for NRTL, NRTL1, and NRTL2 models, are very satisfactory, with global values of 0.0031, 0.0020, and 0.0053 for 187 tie-lines respectively. The obtained rmsd values for the NRTL model using the GA method are better than those reported in the literature. The rmsd results for the three studied models show that NRTL1 can handle the LLE calculations with more accuracy than the original NRTL and NRTL2 activity coefficient models.

KW - Genetic algorithm

KW - Ionic liquid

KW - NRTL

KW - NRTL1

KW - NRTL2

KW - Parameter estimation

UR - http://www.scopus.com/inward/record.url?scp=84876141721&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84876141721&partnerID=8YFLogxK

U2 - 10.1080/00986445.2012.740533

DO - 10.1080/00986445.2012.740533

M3 - Article

AN - SCOPUS:84876141721

VL - 200

SP - 1102

EP - 1120

JO - Chemical Engineering Communications

JF - Chemical Engineering Communications

SN - 0098-6445

IS - 8

ER -