A combination of multi-fluid mixture models with COSMO-SAC

Jäger, Andreas; Mickoleit, Erik; Breitkopf, Cornelia

doi:10.1016/j.fluid.2018.08.004

Cited by 16 publications

(24 citation statements)

References 73 publications

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“…In addition to the data of Sage and Lacey 57 (red symbols), Fig. 5 shows a comparison of the GERG-2008 11 to more recent experimental data with small, wellcharacterized uncertainties from several authors [58][59][60][61][62][63] covering the same temperature, pressure, and composition ranges. These other data are consistent and are represented far more accurately than the data of Sage and Lacey.…”

Section: Data Assessmentmentioning

confidence: 99%

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EOS-LNG: A Fundamental Equation of State for the Calculation of Thermodynamic Properties of Liquefied Natural Gases

Thol

Richter

May

et al. 2019

Journal of Physical and Chemical Reference Data

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A new mixture model (EOS-LNG) for the accurate representation of thermodynamic property data of multicomponent natural gas mixtures in the liquid state is presented. The mathematical approach of the GERG-2008 equation of state of Kunz and Wagner is adopted and new binary-specific functions for methane + n-butane, methane + isobutane, methane + npentane, and methane + isopentane are developed. The representation of all experimental data available in the literature for the corresponding binary systems is carefully analyzed so that these functions can also be applied at fluid states beyond the liquefied natural gas region. The EOS-LNG represents all available binary and multicomponent data in the liquefied natural gas region within their specified experimental uncertainty, which is significantly more accurate than the GERG-2008 model. The main focus was given to the representation of new density data measured between 100 K and 180 K with a maximum pressure of 10 MPa. Deviations from the EOS-LNG presented here do not exceed 0.02% for binary data and 0.05% for multicomponent systems. Deviations of calculated values from experimental data in other fluid regions are similar to or better than those calculated with the GERG-2008 model.

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Section: Data Assessmentmentioning

confidence: 99%

“…Percentage deviations of experimental data for the binary system C1C2 of Sage and Lacey57 and other accurate data[58][59][60][61][62][63] from the GERG-2008 model. 11Fig.…”

mentioning

confidence: 99%

EOS-LNG: A Fundamental Equation of State for the Calculation of Thermodynamic Properties of Liquefied Natural Gases

Thol

Richter

May

et al. 2019

Journal of Physical and Chemical Reference Data

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“…If accurate data are available, the empirical binary specific departure function α ij r can be fitted to the experimental data, see for example the mixture models for methane + ethane by Kunz and Wagner and for carbon dioxide + water by Gernert and Span . However, if no experimental data are available, no binary specific departure function can be developed and only standard mixing rules for the reducing functions can be applied, which do not necessarily yield good predictive results as demonstrated, for example, by Jäger et al , For screening purposes, a model with better predictive capabilities should be used.…”

Section: Combination Of the Multifluid Mixture Model With Cosmo-sacmentioning

confidence: 99%

“…Jäger et al developed a theoretically based departure function, which allows for the combination of the multifluid mixture model with excess Gibbs energy models such as UNIFAC or COSMO-SAC. , The model reads R = 8.3144628 J mol –1 K –1 is the universal gas constant, g GE E,r is the residual excess Gibbs energy calculated from a g E -model, and b = ∑ i =1 N b i is the covolume of the Soave–Redlich–Kwong equation of state. The reduced density of the mixture δ ref at reference pressure p ref , see Jäger et al, is and the reduced density of component i at reference pressure becomes ρ i ,ref = is the density of the saturated liquid of pure component i at reference pressure p ref . The reference density ρ ref of the mixture can be obtained by assuming ideal mixing behavior The reducing temperature and the reducing density are obtained by linear mixing rules The residual excess Gibbs energy can be calculated from COSMO-SAC models in the following way with γ i ,S r being the residual activity coefficient of component i in a liquid mixture S.…”

Section: Combination Of the Multifluid Mixture Model With Cosmo-sacmentioning

confidence: 99%

“…In this work, possible refrigeration cycles for supplying a cooling power of 1 kW at a temperature of −75 °C using CO 2 as refrigerant are discussed. For the most promising refrigeration cycle, a carrier-fluid screening has been conducted using the recently developed combination of the multifluid mixture model with COSMO-SAC. , Using this model, reference equations of state can be used for all pure fluids considered in the screening and due to the use of COSMO-SAC, the predictive capabilities of this model are superior to the multifluid mixture model with standard mixing rules. , Compared to our previous work, an advanced version of COSMO-SAC is used that considers different strengths of donor–acceptor surface segment combinations. All of the thermodynamic property calculations have been done in the programming language Fortran using the thermophysical property software TREND 4.0 .…”

Section: Introductionmentioning

confidence: 99%

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Carrier-Fluid Screening for a Three-Phase Sublimation Refrigeration Cycle with CO₂ Using Reference Equations of State and COSMO-SAC

2019

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The recently proposed combination of the multifluid mixture model with g E -models is used for investigating possible carrier-fluids for CO 2 for a new type of refrigeration cycle. According to the EU regulation No. 517/2014, placing refrigerants with a global warming potential greater than 2500 on the market is prohibited after January 1, 2020. Cooling applications designed to cool products below −50 °C, for which mostly the refrigerant R-23 with a global warming potential (GWP) of 14800 is used, are an exception. R-23 could be replaced by carbon dioxide (CO 2 , GWP = 1) in a refrigeration cycle in which the CO 2 is expanded into the sublimation region. The CO 2 could be blended with a suitable carrier-fluid in order to prevent blockages due to enrichment of dry ice as well as to increase the heat transfer in the sublimator. A screening for a suitable carrier-fluid has been conducted using the most accurate equations of state available in the multifluid mixture model combined with a version of the predictive g E -model COSMO-SAC that considers different strengths of donor− acceptor surface segment combinations. Some of the carrier-fluids lead to a significantly improved coefficient of performance compared to the process with pure CO 2 .

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A Numerical Algorithm for Calculating Critical Points and Its Application to Predictive Mixture Models and Binary CO$$_2$$ Mixtures

Rath,

Gampe,

Jäger

2023

Int J Thermophys

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The use of supercritical fluids in technical applications requires an accurate knowledge of their critical points. For mixtures, these can deviate significantly and without a linear dependency from the critical points of its individual pure components. Since even small amounts of admixture can have noticeable effects, this not only concerns blends of targeted compositions, but also unintentional mixtures for example caused by impurities. Within this work, a method for the calculation of critical points is presented which focuses on numerical robustness promoting a fast and reliable generation of results. Implemented into the thermodynamic property software TREND, with its mixture modeling capabilities, the method allows a flexible combination of different equations of state and mixture models which also includes predictive approaches. Against the background of an increasing relevance of mixtures based on supercritical CO$$_2$$ 2 (sCO$$_2$$ 2 ) for energy applications, critical lines are calculated and compared against experimental results for selected sCO$$_2$$ 2 -based mixtures recently considered for power plant applications. Herein, several combinations of equations of state (EoS) and mixture models are compared. Critical lines are calculated for the first time in this work with the combination of the multi-fluid mixture model with excess Gibbs energy ($$g^\text {E}$$ g E ) models. It was found that the critical lines calculated with the combination of the multi-fluid mixture model with the $$g^\text {E}$$ g E -model COSMO-SAC yields good predictive results for the investigated CO$$_2$$ 2 mixtures.

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A combination of multi-fluid mixture models with COSMO-SAC

Cited by 16 publications

References 73 publications

EOS-LNG: A Fundamental Equation of State for the Calculation of Thermodynamic Properties of Liquefied Natural Gases

EOS-LNG: A Fundamental Equation of State for the Calculation of Thermodynamic Properties of Liquefied Natural Gases

Carrier-Fluid Screening for a Three-Phase Sublimation Refrigeration Cycle with CO₂ Using Reference Equations of State and COSMO-SAC

A Numerical Algorithm for Calculating Critical Points and Its Application to Predictive Mixture Models and Binary CO$$_2$$ Mixtures

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A combination of multi-fluid mixture models with COSMO-SAC

Cited by 16 publications

References 73 publications

EOS-LNG: A Fundamental Equation of State for the Calculation of Thermodynamic Properties of Liquefied Natural Gases

EOS-LNG: A Fundamental Equation of State for the Calculation of Thermodynamic Properties of Liquefied Natural Gases

Carrier-Fluid Screening for a Three-Phase Sublimation Refrigeration Cycle with CO2 Using Reference Equations of State and COSMO-SAC

A Numerical Algorithm for Calculating Critical Points and Its Application to Predictive Mixture Models and Binary CO$$_2$$ Mixtures

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Carrier-Fluid Screening for a Three-Phase Sublimation Refrigeration Cycle with CO₂ Using Reference Equations of State and COSMO-SAC