Saturated Liquid Densities for 33 Binary Refrigerant Mixtures Based on the ISM Equation of State

Sharafi, Zahra; Boushehri, Ali

doi:10.1007/s10765-005-5577-3

Cited by 6 publications

(3 citation statements)

References 12 publications

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“…Hydro uoroether (HFE) and halogenated alkane (HA) are two adaptive categories of the investigated novel coolant liquids generation. By employing relationships developed by Boushehri and Mason, Sharafi and Boushehri generalized the ISM equation of condition based on the numerical mechanical perturbation concept for liquefied coolant mixes [21,22]. On 33 liquid mixtures containing 12 coolants, the equation of status has been validated.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Modeling in Predicting Liquid Density of the Refrigerant Systems Using Least-Squares Support Vector Machine Approach

Cai

Zhang²,

et al. 2022

International Journal of Chemical Engineering

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A robust machine learning algorithm known as the least-squares support vector machine (LSSVM) model was used to predict the liquid densities of 48 different refrigerant systems. Hence, a massive dataset was gathered using the reports published previously. The proposed model was evaluated via various analyses. Based on the statistical analysis results, the actual values predicted by this model have high accuracy, and the calculated values of RMSE, MRE, STD, and R2 were 0.0116, 0.158, 0.1070, and 0.999, respectively. Moreover, sensitivity analysis was done on the efficient input parameters, and it was found that CF2H2 has the most positive effect on the output parameter (with a relevancy factor of +50.19). Furthermore, for checking the real data accuracy, the technique of leverage was considered, the results of which revealed that most of the considered data are reliable. The power and accuracy of this simple model in predicting liquid densities of different refrigerant systems are high; therefore, it is an appropriate alternative for laboratory data.

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Section: Introductionmentioning

confidence: 99%

Comprehensive Modeling in Predicting Liquid Density of the Refrigerant Systems Using Least-Squares Support Vector Machine Approach

Cai

Zhang²,

et al. 2022

International Journal of Chemical Engineering

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“…In recent years, the thermodynamic properties of refrigerant mixtures have been investigated by several researchers. − Despite its drawbacks, one of the equations of state employed for predicting the PVTx properties of refrigerant mixtures has been the ISM equation of state. ,, …”

Section: Introductionmentioning

confidence: 99%

“…In recent years, the thermodynamic properties of refrigerant mixtures have been investigated by several researchers. [3][4][5][6] Despite its drawbacks, one of the equations of state employed for predicting the PVTx properties of refrigerant mixtures has been the ISM equation of state. 3,5,7 In the present work, the Tao and Mason (TM) equation of state (EOS), 1 which is based on statistical mechanics, is extended to predict the densities of both the liquid and gas phases of refrigerant mixtures, and the results are compared with the ISM 2 and Peng-Robinson 8 (PR) equations of state, as well as with literature data.…”

Section: Introductionmentioning

confidence: 99%

Extension of Tao-Mason Equation of State to Mixtures: Results for PVTx Properties of Refrigerants Fluid Mixtures

Yousefi

Moghadasi

Papari

et al. 2009

Ind. Eng. Chem. Res.

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Tao and Mason (J. Chem. Phys. 1994, 100, 9075-9084) developed a statistical-mechanical-based equation of state (EOS) for pure substances. In the present study, we have successfully extended this EOS to fluid mixtures, selecting refrigerant fluid mixtures as the test systems. The considered refrigerant mixtures are R32 + R125, R32 + R134a, R134a + R152a, R125 + R143a, R125 + R134a, R32 + R227ea, R134a + R290, and R22 + R152a. The second virial coefficient, B(T), necessary for the mixture version of the Tao-Mason (TM) EOS, was determined using a two-parameter corresponding-states correlation obtained from the analysis of the speed of sound data and two constants: the enthalpy of vaporization ∆H vap and the molar density F nb , both at the normal boiling point. Other temperature-dependent quantities, including the correction factor R(T) and van der Waals covolume b(T), were obtained from the Lennard-Jones (12-6) model potential. The cross parameters B 12 (T), R 12 (T), and b 12 (T), required by the EOS for mixtures, were determined with the help of simple combining rules. The constructed mixture version of the TM EOS was extensively tested by comparison with experimental data. The results show that the molar gas and liquid densities of the refrigerant mixtures of interest can be predicted to within 1.3% and 2.69%, respectively, over the temperature range of 253-440 K and the pressure range of 0.33-158 bar. The present EOS was further assessed through comparisons with the Ihm-Song-Mason (ISM) and Peng-Robinson (PR) equations of state. In the gas phase, the TM EOS outperforms the two other equations of state. In the liquid phase, there is no noticeable difference between the TM EOS and the PR EOS, but both work better than the ISM EOS.

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Application of modified Tao-Mason equation of state to refrigerant mixtures

Kiani

Papari

Nowruzian

et al. 2015

Korean J. Chem. Eng.

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Saturated Liquid Densities for 33 Binary Refrigerant Mixtures Based on the ISM Equation of State

Cited by 6 publications

References 12 publications

Comprehensive Modeling in Predicting Liquid Density of the Refrigerant Systems Using Least-Squares Support Vector Machine Approach

Comprehensive Modeling in Predicting Liquid Density of the Refrigerant Systems Using Least-Squares Support Vector Machine Approach

Extension of Tao-Mason Equation of State to Mixtures: Results for PVTx Properties of Refrigerants Fluid Mixtures

Application of modified Tao-Mason equation of state to refrigerant mixtures

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