Predicting vapor-liquid equilibria of CO<sub>2</sub>+HFC binary mixtures by the PR EOS combined with a group contribution model

Q4 Engineering 中国科学技术大学学报 Pub Date : 2023-01-01 DOI:10.52396/justc-2023-0001
Zirui Wu, Lingfeng Shi, Rui Sun, Hua Tian, Xuan Wang, Gequn Shu
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Abstract

CO2+HFC binary mixtures have good performance and environmental friendliness and are considered good alternative working fluids in cooling and power cycle systems. The vapor-liquid phase equilibrium properties are key to the calculation of the enthalpy and entropy of mixtures, which is critical for the analysis of cooling and power cycle systems. To accurately predict the vapor-liquid equilibrium of CO2 and HFC (R23, R32, R41, R125, R134a, R143a, R152a, R161, and R227ea) binary mixtures, a group contribution model based on the excess free energy (GE) mixing rules (PR+MHV1+UNIFAC and PR+LCVM+UNIFAC) is established in this paper. The interaction parameters between groups such as -CO2, -Alkane, -CHF, and -CHF3 are obtained by the vapor-liquid phase equilibrium experiment of CO2 and HFC refrigerants, and these group parameters are critical for predicting their vapor-liquid phase equilibrium properties (the pressures and vapor phase molar fractions). The AARDp value calculated by the PR+LCVM+UNIFAC model is 5.53%, the value of AADy1 is 0.0132, and the AARDp and AADy1 values of the PR+MHV1+UNIFAC model are 7.40% and 0.0229, respectively. However, for the CO2+R32 system, the PR+MHV+UNIFAC prediction model can reproduce the experimental data with lower deviations, and the values of AARDp and AADy1 are 1.53% and 0.0045, respectively. In summary, for CO2+HFC binary mixtures, the PR+LCVM+UNIFAC group contribution model can reproduce the experimental data with lower deviations, but for individual CO2 binary mixtures (such as CO2+R32), the PR+MHV1+UNIFAC model also has unique advantages. According to the prediction results of the group contribution model, the PR+LCVM+UNIFAC model has significantly improved the calculation progress compared with the PR+MHV1+UNIFAC model used in the previous system.
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用PR - EOS结合群贡献模型预测CO<sub>2</sub>+HFC二元混合物的汽液平衡
CO<sub>2 /sub>+HFC二元混合物具有良好的性能和环境友好性,被认为是冷却和动力循环系统中良好的替代工作流体。气液相平衡性质是计算混合物焓和熵的关键,对冷却和动力循环系统的分析至关重要。准确预测CO<sub>2</sub>和HFC (R23、R32、R41、R125、R134a、R143a、R152a、R161、R227ea)二元混合物,建立了基于过量自由能(<i>G</i><sup>E</sup>)混合规则(PR+MHV1+UNIFAC和PR+LCVM+UNIFAC)的群体贡献模型。-CO<sub>2</sub>、-烷烃、-CHF和-CHF<sub>3</sub>由CO<sub>2</sub>和HFC制冷剂,这些基团参数对于预测它们的气液相平衡性质(压力和气相摩尔分数)至关重要。AARD< i>术中;/ i>PR+LCVM+UNIFAC模型计算的值为5.53%,AAD<i>y</i><sub>1</sub>为0.0132,AARD<i>p</i>和AAD< i> y< / i> & lt; sub> 1 & lt; / sub>PR+MHV1+UNIFAC模型的值分别为7.40%和0.0229。而对于CO<sub>2</sub>+R32系统,PR+MHV+UNIFAC预测模型能够以较小的偏差再现实验数据,且AARD<i>p</i>和AAD< i> y< / i> & lt; sub> 1 & lt; / sub>分别为1.53%和0.0045。综上所述,对于CO<sub>2& gt; /sub>+HFC二元混合物,PR+LCVM+UNIFAC群体贡献模型可以以较低的偏差重现实验数据,但对于单个CO<sub>2& gt; /sub>二元混合物(如CO<sub>2</sub>+R32), PR+MHV1+UNIFAC模型也具有独特的优势。从群体贡献模型的预测结果来看,PR+LCVM+UNIFAC模型与之前系统中使用的PR+MHV1+UNIFAC模型相比,计算进度明显提高。
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中国科学技术大学学报
中国科学技术大学学报 Engineering-Mechanical Engineering
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0.40
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5692
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