Bell I H, Welliquet J, Mondejar M E, Bazyleva A, Quoilin S, Haglind F
Applied Chemicals and Materials Division, National Institute of Standards and Technology, Boulder, CO 80305, USA.
Energy Systems Research Unit, University of Liége, Liége, Belgium.
Int J Refrig. 2019;103. doi: https://doi.org/10.1016/j.ijrefrig.2019.04.014.
This work evaluates the performance of the group contribution volume translated Peng-Robinson model when predicting the vapor-liquid equilibrium and single phase densities of 28 commercial refrigerant mixtures with low global warming potential and zero ozone depletion potential. Cubic equations of state, and particularly the Peng-Robinson equation of state, are widely used in the refrigeration industry due to their easy applicability for new substances, and their low computational time, although generally lower prediction accuracies must be expected compared to multiparameter equations of state. The group contribution volume translated Peng-Robinson equation of state combines the Peng-Robinson equation of state with a new attraction term, improved mixing rules using a group contribution approach, and volume translation. The results are compared with the estimates obtained using the non translated Peng-Robinson equation of state, and a multiparameter equation of state.
本研究评估了基团贡献体积平移彭 - 罗宾逊模型在预测28种具有低全球变暖潜能值和零臭氧消耗潜能值的商用制冷剂混合物的气液平衡和单相密度时的性能。状态方程，特别是彭 - 罗宾逊状态方程，在制冷行业中被广泛使用，这是因为它们易于应用于新物质，并且计算时间短，不过与多参数状态方程相比，通常预计其预测精度较低。基团贡献体积平移彭 - 罗宾逊状态方程将彭 - 罗宾逊状态方程与一个新的引力项、采用基团贡献方法改进的混合规则以及体积平移相结合。将结果与使用未平移的彭 - 罗宾逊状态方程和多参数状态方程得到的估计值进行比较。
