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Performance of predictive models in phase equilibria of complex associating systems: PC-SAFT and CEOS/GE

机译:预测模型在复杂关联系统的相平衡中的性能:PC-SAFT和CEOS / GE

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Cubic equations of state combined with excess Gibbs energy predictive models (like UNIFAC) and equations of state based on applied statistical mechanics are among the main alternatives for phase equilibria prediction involving polar substances in wide temperature and pressure ranges. In this work, the predictive performances of the PC-SAFT with association contribution and Peng-Robinson (PR) combined with UNIFAC (Do) through mixing rules are compared. Binary and multi-component systems involving polar and non-polar substances were analyzed. Results were also compared to experimental data available in the literature. Results show a similar predictive performance for PC-SAFT with association and cubic equations combined with UNIFAC (Do) through mixing rules. Although PC-SAFT with association requires less parameters, it is more complex and requires more computation time.
机译:立方状态方程与多余的吉布斯能量预测模型(例如UNIFAC)相结合,以及基于应用统计力学的状态方程,是在宽温度和压力范围内涉及极性物质的相平衡预测的主要替代方法。在这项工作中,通过混合规则比较了PC-SAFT具有关联贡献和Peng-Robinson(PR)结合UNIFAC(Do)的预测性能。分析了涉及极性和非极性物质的二元和多组分系统。还将结果与文献中提供的实验数据进行了比较。结果显示,通过混合规则,结合了联合方程和三次方程式并结合UNIFAC(Do)的PC-SAFT具有相似的预测性能。尽管具有关联的PC-SAFT需要较少的参数,但是它更复杂并且需要更多的计算时间。

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