Xiao Xiong, Yang Xiaoxian
Fluid Science & Resources Division, Department of Chemical Engineering, The University of Western Australia, Crawley, WA 6009, Australia.
Chemnitz University of Technology, Applied Thermodynamics, 09107 Chemnitz, Germany.
ACS Omega. 2025 Jun 27;10(27):29021-29036. doi: 10.1021/acsomega.5c01157. eCollection 2025 Jul 15.
Accurate prediction of viscosity remains a challenge in industry due to the lack of reliable simple universal models. This work investigates the accuracy of four cubic equations of state (EOS) with different α functions for pure fluid viscosity predictions based on the residual entropy scaling (RES). The cubic EOS are Peng-Robinson (PR), Soave-Redlich-Kwong (SRK), Patel-Teja-Valderrama (PTV), and Yang-Frotscher-Richter (YFR), and the α functions are those proposed by Twu et al., Coquelet et al., Mahmoodi and Sedigh, and Heyen et al. The investigation utilizes the approximately 54,000 experimental viscosity data of 124 pure fluids at pressures below 60 MPa, mainly obtained from the NIST TDE (ThermoData Engine) database. Compared to a previous study (ACS Omega2025, 10, 6124), which focused on the Soave α function, the adoption of modified α functions led to improved viscosity predictions for 39 out of the 124 studied substances. Notable enhancements are observed for R1234ze-(E) and SO with PTV-Heyen and for CO with PR-Twu. The absolute average deviation (AAD) between experimental values and model predictions is 3.1% (PR, SRK, and YFR), 3.0% (PTV), 3.4% (PR-Twu and SRK-Coquelet), 3.2% (PTV-Heyen and SRK-MS), 3.5% (PR-Coquelet), and 3.3% (PR-MS). As a reference, the AAD of the various reference models implemented in REFPROP 10.0 is 2.7%. This work demonstrates the potential of integrating optimized α functions to improve the predictive capabilities for viscosity within the cubic EOS + RES framework for certain specific pure fluids. Additionally, a recommended combination of cubic EOS and α function is provided for each fluid studied.
由于缺乏可靠的简单通用模型，准确预测粘度在工业中仍然是一项挑战。本研究基于残余熵标度（RES），研究了四种具有不同α函数的立方状态方程（EOS）对纯流体粘度预测的准确性。立方EOS分别为彭-罗宾逊（PR）、索阿韦-雷德利希-邝（SRK）、帕特尔-特贾-巴尔德拉马（PTV）和杨-弗罗切尔-里希特（YFR），α函数分别是由Twu等人、科克莱特等人、马哈茂迪和塞迪格以及海恩等人提出的。该研究利用了124种纯流体在压力低于60MPa时约54000个实验粘度数据，这些数据主要来自美国国家标准与技术研究院的热数据引擎（NIST TDE）数据库。与之前一项专注于索阿韦α函数的研究（《美国化学会奥米加》2025年，10卷，6124页）相比，采用改进后的α函数使得在所研究的124种物质中有39种的粘度预测得到了改善。对于R1234ze-(E)和SO，使用PTV-海恩模型有显著改进；对于CO，使用PR-Twu模型有显著改进。实验值与模型预测值之间的绝对平均偏差（AAD）分别为：PR、SRK和YFR为3.1%，PTV为3.0%，PR-Twu和SRK-科克莱特为3.4%，PTV-海恩和SRK-MS为3.2%，PR-科克莱特为3.5%，PR-MS为3.3%。作为参考，REFPROP 10.0中实施的各种参考模型的AAD为2.7%。这项研究证明了在立方EOS + RES框架内，整合优化后的α函数以提高某些特定纯流体粘度预测能力的潜力。此外，还为每种研究的流体提供了立方EOS和α函数的推荐组合。
