Entropy Scaling of Viscosity IV-Application to 124 Industrially Important Fluids.

IF 2.1 3区 工程技术 Q3 CHEMISTRY, MULTIDISCIPLINARY Journal of Chemical & Engineering Data Pub Date : 2025-01-10 eCollection Date: 2025-02-13 DOI:10.1021/acs.jced.4c00451
Viktor Martinek, Ian Bell, Roland Herzog, Markus Richter, Xiaoxian Yang
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Abstract

In our previous work [Yang X.J. Chem. Eng. Data2021, 66, 1385-1398], a residual entropy scaling (RES) approach was developed to link viscosity to residual entropy using a 4-term power function for 39 refrigerants. In further research [Yang X.Int. J. Thermophys.2022, 43, 183], this RES approach was extended to 124 pure fluids containing fluids from light gases (hydrogen and helium) to dense fluids (e.g., heavy hydrocarbons) and fluids with strong association force (e.g., water). In these previous research studies, the model was developed by manual optimization of the power function. The average absolute relative deviation (AARD) of experimental data from the RES model is approximately 3.36%, which is higher than the 2.74% obtained with the various models in REFPROP 10.0. In the present work, the power function was optimized by iteratively fitting the global (fluid-independent power terms) and local parameters (fluid-specific and group-specific parameters) and screening the experimental data. The resulting equation has only three terms instead of four. Most notably, the AARD of the new RES model is reduced down to 2.76%; this is very close to the various multiparameter models in REFPROP 10.0, while the average relative deviation (ARD) amounts to 0.03%, which is smaller than REFPROP 10.0's 0.7%. A Python package is provided for the use of the developped model.

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粘度的熵标度iv -在124种工业重要流体中的应用。
在我们之前的工作中[j]。Eng。[j],利用四项幂函数将39种制冷剂的粘度与剩余熵联系起来,建立了一种剩余熵缩放(RES)方法。在进一步的研究中[j]。[j] .热物理学报,2022,43,183],将这种RES方法扩展到124种纯流体,其中包括轻气体(氢和氦)、致密流体(如重碳氢化合物)和强结合力流体(如水)。在以往的研究中,模型都是通过手工优化幂函数来建立的。实验数据与RES模型的平均绝对相对偏差(AARD)约为3.36%,高于REFPROP 10.0中各种模型得到的2.74%。在本工作中,通过迭代拟合全局(与流体无关的功率项)和局部参数(流体特定参数和群体特定参数)并筛选实验数据来优化功率函数。得到的方程只有三项而不是四项。值得注意的是,新RES模型的AARD降至2.76%;这与REFPROP 10.0中的各种多参数模型非常接近,而平均相对偏差(ARD)为0.03%,小于REFPROP 10.0的0.7%。为使用开发的模型提供了一个Python包。
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来源期刊
Journal of Chemical & Engineering Data
Journal of Chemical & Engineering Data 工程技术-工程:化工
CiteScore
5.20
自引率
19.20%
发文量
324
审稿时长
2.2 months
期刊介绍: The Journal of Chemical & Engineering Data is a monthly journal devoted to the publication of data obtained from both experiment and computation, which are viewed as complementary. It is the only American Chemical Society journal primarily concerned with articles containing data on the phase behavior and the physical, thermodynamic, and transport properties of well-defined materials, including complex mixtures of known compositions. While environmental and biological samples are of interest, their compositions must be known and reproducible. As a result, adsorption on natural product materials does not generally fit within the scope of Journal of Chemical & Engineering Data.
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