Prediction for Critical Temperature and Critical Pressure of Mixtures by Improved Empirical Correlations

IF 2.5 4区 工程技术 Q3 CHEMISTRY, PHYSICAL
Bo Tang, Xueqiang Dong, Yanxing Zhao, Maoqiong Gong
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引用次数: 0

Abstract

Vapor–liquid critical properties of mixtures are key parameters in the petrochemical industry and supercritical technology. Experimental measurements and theoretical calculations are the primary methods for determining the critical parameters of mixtures. However, existing empirical correlations to quickly predict the critical temperatures and pressures of mixtures are limited by critical volume data for pure substances. In this work, improved methods of Li method and Kreglewski–Li (KL) method are proposed. Improved methods do not require critical volume data for pure substances, but replace it with acentric factors, normal boiling points, or critical temperatures of pure substances that are easier to obtain and more accurate. About 9,000 critical temperature and critical pressure data points for binary and ternary mixtures were collected to compare and evaluate the Li method, KL method, and improved methods. Notably, the improved methods are only applicable to the class I and II mixtures according to the classification of Van Konynenburg and Scott. Overall, compared with the original method, both Improvement 3 (critical volumes for pure substances of Li method and KL method are replaced with critical temperatures of pure substances) and Improvement 4 (critical volumes for pure substances of Li method and KL method are replaced with normal boiling points of pure substances) greatly improve the accuracy. Meanwhile, when predicting critical temperatures and critical pressures, Improvement 3 not only reduces the input thermophysical property parameters but also improves the prediction accuracy. Among the improved methods, Improvement 4 shows the highest prediction accuracy. The average absolute relative deviation (AARD) and average absolute deviation (AAD) of Improvement 4 for predicting the critical temperatures of binary and ternary mixtures are 1.88%, 7.83 K, 1.60%, and 7.63 K, respectively. The AARD and AAD for predicting the critical temperature of the binary mixtures composed of two pure substances with both acentric factors greater than 0.0955 by Improvement 4 are 1.56% and 7.33 K. The AARD and AAD of Improvement 4 for predicting the critical pressures of binary and ternary mixtures are 4.34%, 0.30 MPa, 3.70%, and 0.19 MPa, respectively. The optimal model selection depends on the specific mixture type under consideration when using improved methods specifically.

Graphical abstract

用改进的经验关系式预测混合物临界温度和临界压力
混合气液临界性质是石油化工和超临界技术中的关键参数。实验测量和理论计算是确定混合物临界参数的主要方法。然而,现有的快速预测混合物临界温度和压力的经验关联受到纯物质临界体积数据的限制。本文提出了Li法和Kreglewski-Li (KL)法的改进方法。改进的方法不需要纯物质的临界体积数据,而是用更容易获得和更准确的纯物质的非中心因子、正常沸点或临界温度来代替。收集了近9000个二元和三元混合物的临界温度和临界压力数据点,对Li法、KL法和改进方法进行了比较和评价。值得注意的是,根据Van Konynenburg和Scott的分类,改进的方法只适用于I类和II类混合物。总体而言,与原方法相比,改进3(将Li法和KL法的纯物质临界体积替换为纯物质的临界温度)和改进4(将Li法和KL法的纯物质临界体积替换为纯物质的正常沸点)大大提高了精度。同时,在预测临界温度和临界压力时,改进3不仅减少了输入的热物性参数,而且提高了预测精度。其中,改进方法4的预测精度最高。改进4预测二元和三元混合物临界温度的平均绝对相对偏差(AARD)和平均绝对偏差(AAD)分别为1.88%、7.83 K、1.60%和7.63 K。改进4对非中心因子均大于0.0955的两种纯物质组成的二元混合物的临界温度预测的AARD和AAD分别为1.56%和7.33 K。改进4预测二元和三元混合物临界压力的AAD和AAD分别为4.34%、0.30 MPa、3.70%和0.19 MPa。在具体使用改进方法时,模型的最优选择取决于所考虑的具体混合类型。图形抽象
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来源期刊
CiteScore
4.10
自引率
9.10%
发文量
179
审稿时长
5 months
期刊介绍: International Journal of Thermophysics serves as an international medium for the publication of papers in thermophysics, assisting both generators and users of thermophysical properties data. This distinguished journal publishes both experimental and theoretical papers on thermophysical properties of matter in the liquid, gaseous, and solid states (including soft matter, biofluids, and nano- and bio-materials), on instrumentation and techniques leading to their measurement, and on computer studies of model and related systems. Studies in all ranges of temperature, pressure, wavelength, and other relevant variables are included.
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