报告摘要： Oil, as a key component in compressors, plays an important role in many systems like heat pump and organic Rankin cycle. Modelling all required thermophysical properties – mainly density, phase behavior, heat capacity, entropy, enthalpy, viscosity and thermal conductivity – of an oil and the oil + working fluid (typically refrigerant) mixtures remains a challenge today. Here, we propose a novel modelling approach that requires less than 20 (at least 12) experimental points to develop a model set for all required properties of an oil, and one additional mixture data to enable mixture prediction. The residual entropy scaling approach is extensively improved for the best possible viscosity and thermal conductivity calculation. For quasi-pure oils, this approach has an estimated uncertainty of 7 % for viscosity and 3 % for all other properties. For binary systems, except for viscosity, this approach still yields good prediction, typically within 8 %. With the developed modelling approach, the impact on the thermo-economic performance of a thermodynamic cycle when working fluids are mixed with oils are investigated.

报告人简介：Dr. Xiaoxan Yang got his PhD degree in Tsinghua University, China. He then became a postdoc fellow in Ruhr University Bochum, a research associate in the University of Western Australia, and now is doing habilitation in Technology University Chemnitz. His research focuses on accurate thermophysical property measurements and modelling, as well as gas adsorption experiments and pressure swing adsorption simulation. He is currently focusing on thermophysical property modelling of refrigerants and their mixtures with lubricant oils. His presentation today is Fluid property models for thermo-economic analysis of thermodynamic cycles – considering oil effects.