Systematic identification method for data analysis and phase equilibria modelling for lipids systems

Olivia A. Perederic, Larissa P. Cunico, Sawitree Kalakul, Bent Sarup, John M. Woodley, Georgios M. Kontogeorgis*, Rafiqul Gani

*Corresponding author for this work

Research output: Contribution to journalJournal articleResearchpeer-review

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Abstract

Industrial use of lipids has been increasing as a consequence of increased developments related to biobased economies. In addition to applications in food-products, lipids are used by many industrial sectors, for example, biodiesel, edible oil, health, and personal care. Phase equilibria predictions for chemical systems with lipids play a major role in process–product modelling, simulation and design. Due to the large number of lipid-compounds involved, predictive methods like group contribution based methods are particularly suitable for estimation of pure compound and mixture properties that may not be available. Limited experimental data availability and poor performances of currently available group contribution based methods is therefore an obstacle for obtaining the necessary information regarding phase equilibria of chemical systems with lipids. In this paper, a systematic identification-regression method (to be called identification method) for phase equilibrium modelling, where, based on the available experimentally measured phase equilibrium data, the selected model parameters are estimated in a hierarchical and efficient manner, is presented. The aim of the method is to improve the quality of phase equilibria prediction for the selected group contribution based methods. By applying the identification method, a newset of binary group interaction parameters regressed from vapour-liquid equilibrium data for chemical systems with lipids is presented for the Original UNIFAC model, together with regression statistics and model performance. An extended and updated version of the in-house SPEED Lipids database, which is used for the needed pure compound properties and phase equilibria data, is also presented
Original languageEnglish
JournalJournal of Chemical Thermodynamics
Volume121
Pages (from-to)153-169
ISSN0021-9614
DOIs
Publication statusPublished - 2018

Keywords

  • UNIFAC
  • Lipids
  • Vapour-liquid equilibria
  • Solid-liquid equilibria
  • Parameter estimation

Cite this

@article{b1b5fa795b794174b1e2eaa1af6bf783,
title = "Systematic identification method for data analysis and phase equilibria modelling for lipids systems",
abstract = "Industrial use of lipids has been increasing as a consequence of increased developments related to biobased economies. In addition to applications in food-products, lipids are used by many industrial sectors, for example, biodiesel, edible oil, health, and personal care. Phase equilibria predictions for chemical systems with lipids play a major role in process–product modelling, simulation and design. Due to the large number of lipid-compounds involved, predictive methods like group contribution based methods are particularly suitable for estimation of pure compound and mixture properties that may not be available. Limited experimental data availability and poor performances of currently available group contribution based methods is therefore an obstacle for obtaining the necessary information regarding phase equilibria of chemical systems with lipids. In this paper, a systematic identification-regression method (to be called identification method) for phase equilibrium modelling, where, based on the available experimentally measured phase equilibrium data, the selected model parameters are estimated in a hierarchical and efficient manner, is presented. The aim of the method is to improve the quality of phase equilibria prediction for the selected group contribution based methods. By applying the identification method, a newset of binary group interaction parameters regressed from vapour-liquid equilibrium data for chemical systems with lipids is presented for the Original UNIFAC model, together with regression statistics and model performance. An extended and updated version of the in-house SPEED Lipids database, which is used for the needed pure compound properties and phase equilibria data, is also presented",
keywords = "UNIFAC, Lipids, Vapour-liquid equilibria, Solid-liquid equilibria, Parameter estimation",
author = "Perederic, {Olivia A.} and Cunico, {Larissa P.} and Sawitree Kalakul and Bent Sarup and Woodley, {John M.} and Kontogeorgis, {Georgios M.} and Rafiqul Gani",
year = "2018",
doi = "10.1016/j.jct.2018.02.007",
language = "English",
volume = "121",
pages = "153--169",
journal = "Journal of Chemical Thermodynamics",
issn = "0021-9614",
publisher = "Academic Press",

}

Systematic identification method for data analysis and phase equilibria modelling for lipids systems. / Perederic, Olivia A.; Cunico, Larissa P.; Kalakul, Sawitree; Sarup, Bent; Woodley, John M.; Kontogeorgis, Georgios M.; Gani, Rafiqul.

In: Journal of Chemical Thermodynamics, Vol. 121, 2018, p. 153-169.

Research output: Contribution to journalJournal articleResearchpeer-review

TY - JOUR

T1 - Systematic identification method for data analysis and phase equilibria modelling for lipids systems

AU - Perederic, Olivia A.

AU - Cunico, Larissa P.

AU - Kalakul, Sawitree

AU - Sarup, Bent

AU - Woodley, John M.

AU - Kontogeorgis, Georgios M.

AU - Gani, Rafiqul

PY - 2018

Y1 - 2018

N2 - Industrial use of lipids has been increasing as a consequence of increased developments related to biobased economies. In addition to applications in food-products, lipids are used by many industrial sectors, for example, biodiesel, edible oil, health, and personal care. Phase equilibria predictions for chemical systems with lipids play a major role in process–product modelling, simulation and design. Due to the large number of lipid-compounds involved, predictive methods like group contribution based methods are particularly suitable for estimation of pure compound and mixture properties that may not be available. Limited experimental data availability and poor performances of currently available group contribution based methods is therefore an obstacle for obtaining the necessary information regarding phase equilibria of chemical systems with lipids. In this paper, a systematic identification-regression method (to be called identification method) for phase equilibrium modelling, where, based on the available experimentally measured phase equilibrium data, the selected model parameters are estimated in a hierarchical and efficient manner, is presented. The aim of the method is to improve the quality of phase equilibria prediction for the selected group contribution based methods. By applying the identification method, a newset of binary group interaction parameters regressed from vapour-liquid equilibrium data for chemical systems with lipids is presented for the Original UNIFAC model, together with regression statistics and model performance. An extended and updated version of the in-house SPEED Lipids database, which is used for the needed pure compound properties and phase equilibria data, is also presented

AB - Industrial use of lipids has been increasing as a consequence of increased developments related to biobased economies. In addition to applications in food-products, lipids are used by many industrial sectors, for example, biodiesel, edible oil, health, and personal care. Phase equilibria predictions for chemical systems with lipids play a major role in process–product modelling, simulation and design. Due to the large number of lipid-compounds involved, predictive methods like group contribution based methods are particularly suitable for estimation of pure compound and mixture properties that may not be available. Limited experimental data availability and poor performances of currently available group contribution based methods is therefore an obstacle for obtaining the necessary information regarding phase equilibria of chemical systems with lipids. In this paper, a systematic identification-regression method (to be called identification method) for phase equilibrium modelling, where, based on the available experimentally measured phase equilibrium data, the selected model parameters are estimated in a hierarchical and efficient manner, is presented. The aim of the method is to improve the quality of phase equilibria prediction for the selected group contribution based methods. By applying the identification method, a newset of binary group interaction parameters regressed from vapour-liquid equilibrium data for chemical systems with lipids is presented for the Original UNIFAC model, together with regression statistics and model performance. An extended and updated version of the in-house SPEED Lipids database, which is used for the needed pure compound properties and phase equilibria data, is also presented

KW - UNIFAC

KW - Lipids

KW - Vapour-liquid equilibria

KW - Solid-liquid equilibria

KW - Parameter estimation

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DO - 10.1016/j.jct.2018.02.007

M3 - Journal article

VL - 121

SP - 153

EP - 169

JO - Journal of Chemical Thermodynamics

JF - Journal of Chemical Thermodynamics

SN - 0021-9614

ER -