Bell Ian H
Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, CO 80305.
J Chem Eng Data. 2020;65(6). doi: 10.1021/acs.jced.0c00209.
In this work, a broadly-applicable and simple approach for building high accuracy viscosity correlations is demonstrated for propane. The approach is based on the combination of a number of recent insights related to the use of residual entropy scaling, especially a new way of scaling the viscosity for consistency with the dilute-gas limit. With three adjustable parameters in the dense phase, the primary viscosity data for propane are predicted with a mean absolute relative deviation of 1.38%, and 95% of the primary data are predicted within a relative error band of less than 5%. The dimensionality of the dense-phase contribution is reduced from the conventional two dimensional approach (temperature and density) to a one-dimensional correlation with residual entropy as the independent variable. The simplicity of the model formulation ensures smooth extrapolation behavior (barring errors in the equation of state itself). The approach proposed here should be applicable to a wide range of chemical species. The supporting information includes the relevant data in tabular form and a Python implementation of the model.
在这项工作中,展示了一种广泛适用且简单的方法来构建高精度的丙烷粘度关联式。该方法基于与剩余熵标度使用相关的一些最新见解的结合,特别是一种新的粘度标度方式,以与稀薄气体极限保持一致。通过在密相中有三个可调参数,丙烷的主要粘度数据得以预测,平均绝对相对偏差为1.38%,并且95%的主要数据在相对误差带小于5%的范围内被预测。密相贡献的维度从传统的二维方法(温度和密度)减少到以剩余熵为自变量的一维关联式。模型公式的简单性确保了平滑的外推行为(除非状态方程本身存在误差)。这里提出的方法应该适用于广泛的化学物种。支持信息包括表格形式的相关数据以及该模型的Python实现。