A theoretically based departure function for multi-fluid mixture models
Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Jäger, Andreas [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2018transfer abstract |
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| Schlagwörter: |
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| Umfang: |
14 |
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| Übergeordnetes Werk: |
Enthalten in: Fabrication and compressive behaviour of an aluminium foam composite - Li, Yong-gang ELSEVIER, 2015, an international journal, New York, NY [u.a.] |
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| Übergeordnetes Werk: |
volume:469 ; year:2018 ; day:15 ; month:08 ; pages:56-69 ; extent:14 |
| Links: |
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| DOI / URN: |
10.1016/j.fluid.2018.04.015 |
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ELV043003516 |
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| 520 | |a Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. | ||
| 520 | |a Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. | ||
| 650 | 7 | |a Vapor-liquid equilibria |2 Elsevier | |
| 650 | 7 | |a UNIFAC |2 Elsevier | |
| 650 | 7 | |a Excess Gibbs energy |2 Elsevier | |
| 650 | 7 | |a Theoretically based departure function |2 Elsevier | |
| 650 | 7 | |a Multi-fluid mixture model |2 Elsevier | |
| 650 | 7 | |a Excess Helmholtz energy |2 Elsevier | |
| 650 | 7 | |a Reference equations of state |2 Elsevier | |
| 700 | 1 | |a Bell, Ian H. |4 oth | |
| 700 | 1 | |a Breitkopf, Cornelia |4 oth | |
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10.1016/j.fluid.2018.04.015 doi GBV00000000000228A.pica (DE-627)ELV043003516 (ELSEVIER)S0378-3812(18)30162-6 DE-627 ger DE-627 rakwb eng 660 540 660 DE-600 540 DE-600 670 VZ 540 VZ 630 VZ Jäger, Andreas verfasserin aut A theoretically based departure function for multi-fluid mixture models 2018transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Vapor-liquid equilibria Elsevier UNIFAC Elsevier Excess Gibbs energy Elsevier Theoretically based departure function Elsevier Multi-fluid mixture model Elsevier Excess Helmholtz energy Elsevier Reference equations of state Elsevier Bell, Ian H. oth Breitkopf, Cornelia oth Enthalten in Science Direct Li, Yong-gang ELSEVIER Fabrication and compressive behaviour of an aluminium foam composite 2015 an international journal New York, NY [u.a.] (DE-627)ELV013241125 volume:469 year:2018 day:15 month:08 pages:56-69 extent:14 https://doi.org/10.1016/j.fluid.2018.04.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_31 GBV_ILN_40 GBV_ILN_100 GBV_ILN_136 AR 469 2018 15 0815 56-69 14 045F 660 |
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10.1016/j.fluid.2018.04.015 doi GBV00000000000228A.pica (DE-627)ELV043003516 (ELSEVIER)S0378-3812(18)30162-6 DE-627 ger DE-627 rakwb eng 660 540 660 DE-600 540 DE-600 670 VZ 540 VZ 630 VZ Jäger, Andreas verfasserin aut A theoretically based departure function for multi-fluid mixture models 2018transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Vapor-liquid equilibria Elsevier UNIFAC Elsevier Excess Gibbs energy Elsevier Theoretically based departure function Elsevier Multi-fluid mixture model Elsevier Excess Helmholtz energy Elsevier Reference equations of state Elsevier Bell, Ian H. oth Breitkopf, Cornelia oth Enthalten in Science Direct Li, Yong-gang ELSEVIER Fabrication and compressive behaviour of an aluminium foam composite 2015 an international journal New York, NY [u.a.] (DE-627)ELV013241125 volume:469 year:2018 day:15 month:08 pages:56-69 extent:14 https://doi.org/10.1016/j.fluid.2018.04.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_31 GBV_ILN_40 GBV_ILN_100 GBV_ILN_136 AR 469 2018 15 0815 56-69 14 045F 660 |
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10.1016/j.fluid.2018.04.015 doi GBV00000000000228A.pica (DE-627)ELV043003516 (ELSEVIER)S0378-3812(18)30162-6 DE-627 ger DE-627 rakwb eng 660 540 660 DE-600 540 DE-600 670 VZ 540 VZ 630 VZ Jäger, Andreas verfasserin aut A theoretically based departure function for multi-fluid mixture models 2018transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Vapor-liquid equilibria Elsevier UNIFAC Elsevier Excess Gibbs energy Elsevier Theoretically based departure function Elsevier Multi-fluid mixture model Elsevier Excess Helmholtz energy Elsevier Reference equations of state Elsevier Bell, Ian H. oth Breitkopf, Cornelia oth Enthalten in Science Direct Li, Yong-gang ELSEVIER Fabrication and compressive behaviour of an aluminium foam composite 2015 an international journal New York, NY [u.a.] (DE-627)ELV013241125 volume:469 year:2018 day:15 month:08 pages:56-69 extent:14 https://doi.org/10.1016/j.fluid.2018.04.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_31 GBV_ILN_40 GBV_ILN_100 GBV_ILN_136 AR 469 2018 15 0815 56-69 14 045F 660 |
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10.1016/j.fluid.2018.04.015 doi GBV00000000000228A.pica (DE-627)ELV043003516 (ELSEVIER)S0378-3812(18)30162-6 DE-627 ger DE-627 rakwb eng 660 540 660 DE-600 540 DE-600 670 VZ 540 VZ 630 VZ Jäger, Andreas verfasserin aut A theoretically based departure function for multi-fluid mixture models 2018transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Vapor-liquid equilibria Elsevier UNIFAC Elsevier Excess Gibbs energy Elsevier Theoretically based departure function Elsevier Multi-fluid mixture model Elsevier Excess Helmholtz energy Elsevier Reference equations of state Elsevier Bell, Ian H. oth Breitkopf, Cornelia oth Enthalten in Science Direct Li, Yong-gang ELSEVIER Fabrication and compressive behaviour of an aluminium foam composite 2015 an international journal New York, NY [u.a.] (DE-627)ELV013241125 volume:469 year:2018 day:15 month:08 pages:56-69 extent:14 https://doi.org/10.1016/j.fluid.2018.04.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_31 GBV_ILN_40 GBV_ILN_100 GBV_ILN_136 AR 469 2018 15 0815 56-69 14 045F 660 |
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10.1016/j.fluid.2018.04.015 doi GBV00000000000228A.pica (DE-627)ELV043003516 (ELSEVIER)S0378-3812(18)30162-6 DE-627 ger DE-627 rakwb eng 660 540 660 DE-600 540 DE-600 670 VZ 540 VZ 630 VZ Jäger, Andreas verfasserin aut A theoretically based departure function for multi-fluid mixture models 2018transfer abstract 14 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. Vapor-liquid equilibria Elsevier UNIFAC Elsevier Excess Gibbs energy Elsevier Theoretically based departure function Elsevier Multi-fluid mixture model Elsevier Excess Helmholtz energy Elsevier Reference equations of state Elsevier Bell, Ian H. oth Breitkopf, Cornelia oth Enthalten in Science Direct Li, Yong-gang ELSEVIER Fabrication and compressive behaviour of an aluminium foam composite 2015 an international journal New York, NY [u.a.] (DE-627)ELV013241125 volume:469 year:2018 day:15 month:08 pages:56-69 extent:14 https://doi.org/10.1016/j.fluid.2018.04.015 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA GBV_ILN_31 GBV_ILN_40 GBV_ILN_100 GBV_ILN_136 AR 469 2018 15 0815 56-69 14 045F 660 |
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a theoretically based departure function for multi-fluid mixture models |
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A theoretically based departure function for multi-fluid mixture models |
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Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. |
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Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. |
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Multi-fluid mixture models for highly accurate multiparameter equations of state have been applied very successfully in the past years in order to accurately model thermophysical properties of mixtures. The multi-fluid mixture model mainly relies on empirical reducing functions and for some mixtures also on departure functions, for which the mathematical structure is a priori unknown and thus must be determined during the fitting procedure. By applying standard mixing rules for the reducing functions and by omitting the departure function, the mixture model can also be used predictively. However, it is demonstrated in this work that the predictive capability of this type of mixture model is rather limited. Therefore, a new model is proposed, which is a combination of the multi-fluid model with excess Gibbs energy models. This new approach results in a theoretically based formulation for the departure function of the multi-fluid model. It is shown that the new model yields very good results for the description of binary mixtures of the components ethanol, ethane, carbon dioxide, propene, and benzene. While the state-of-the-art multi-fluid model with either predictive linear mixing rules or Lorentz-Berthelot combining rules for the parameters of the reducing functions does not represent the phase equilibria for the investigated binary mixtures well, and in case of the azeotropes predicts qualitatively wrong mixture behavior, the new model is capable of accurately representing the phase equilibria of all binary mixtures investigated. |
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