基于剩余熵黏度标度理论预测混合制冷工质黏度

康凯; 谷雅秀; 王晓坡

doi:10.7652/xjtuxb202112021

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基于剩余熵黏度标度理论预测混合制冷工质黏度

更新时间：2025-07-09

- 基于剩余熵黏度标度理论预测混合制冷工质黏度
- A Viscosity Model of Refrigerant Mixtures Based on Excess Entropy Scaling Method
- 西安交通大学学报 2021年55卷第12期页码：180-188
- 作者机构：
  
  长安大学建筑工程学院,西安,710061
- 作者简介：
- 基金信息：
  
  : 2021-03-23。作者简介: 康凯(1991—),男,讲师。基金项目: 国家自然科学基金资助项目(52006015);中央高校基本科研业务费资助项目(300102281302,300102289203)
- DOI：10.7652/xjtuxb202112021
  中图分类号： TK121
- 网络首发：2021-12-10，
  
  纸质出版：2021
- 稿件说明：
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康凯, 谷雅秀, 王晓坡. 基于剩余熵黏度标度理论预测混合制冷工质黏度[J]. 西安交通大学学报, 2021,55(12):180-188.

A Viscosity Model of Refrigerant Mixtures Based on Excess Entropy Scaling Method[J]. 2021, 55(12): 180-188.
康凯, 谷雅秀, 王晓坡. 基于剩余熵黏度标度理论预测混合制冷工质黏度[J]. 西安交通大学学报, 2021,55(12):180-188. DOI： 10.7652/xjtuxb202112021.

A Viscosity Model of Refrigerant Mixtures Based on Excess Entropy Scaling Method[J]. 2021, 55(12): 180-188. DOI： 10.7652/xjtuxb202112021.

摘要

为了获得不同工况新型环保混合制冷工质黏度基础数据

为工业过程设计、系统优化以及设备研发提供技术支持

利用简化版扰动链统计缔合流体理论

构建包括氢氟烯烃(HFO)、氢氟烃(HFC)、烷烃和CO

在内的11种制冷工质无量纲对比黏度与系统剩余熵的函数关系

系统研究了汽液相平衡性质和可能存在的受分子结构及静电分布影响的高度非理想黏度性质

并结合带有预测性的混合法则将本文提出的纯质模型参数推广至多元复杂体系。结果表明:针对所研究的多元复杂体系

除去部分近临界区含CO

系统外

模型预测值与文献数据间最大绝对平均偏差小于5.1%。该模型可以精确预测远临界区不同工况下混合制冷工质的黏度数据

能够有效补充现有实验数据的不足

但对处于近临界区工况的复杂体系

该模型仍需进一步改进。

Abstract

In order to obtain reliable basic viscosity data of the new environment mixed refrigeration working medium and to provide technical support for industrial process design

system optimization and equipment research and development

the simplified perturbed-chain statistical association fluid theory is used to establish the function relationship between the reduced residual entropy and the dimensionless reduced viscosity of 11 refrigerants

including hydrofluorolefins

hydrofluorocarbons

alkanes and CO

. The vapor-liquid equilibrium properties and the possible highly non-ideal viscosity properties affected by molecular structure and electrostatic distribution are systematically studied. The parameters of pure compounds are extended to multivariate

complex system by combining the predictive mixing rule. The results show that the maximum absolute mean deviation between the predicted viscosities from the model and the experimental data is less than 5.1% for the multivariate complex system

except for some systems containing CO

in the near critical point. It is verified that the proposed model is capable of predicting the viscosity of complex refrigerant mixtures far away from the critical region. However

the model still needs to be further improved for the complex system in the near critical zone.

关键词

Keywords

references

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