(364d) Systematic Evaluation of Thermophysical Properties of Low GWP Refrigerants and Blends for Refrigeration Cooling Systems By Molecular Modeling Techniques
AIChE Annual Meeting
2019 AIChE Annual Meeting
Engineering Sciences and Fundamentals
Thermophysical Properties and Phase Behavior
Tuesday, November 12, 2019 - 1:48pm to 2:06pm
Most of the currently in place and proposed regulations (F-Gas in the European Union and CARB and EC in North America)  target refrigerants to be used that do not exceed 150 GWP for refrigeration and 750 GWP for air conditioning applications, thus creating an immediate demand for developing fourth generation refrigerants with low GWPs. The major perceived barriers to these low-GWP alternatives include safety (i.e., flammability, corrosion, toxicity), first cost and return on investment. In response to this need, hydrofluoroolefins (HFOs) and some third generation refrigerants blends have been included in the NIST list as the most environmental friendlier candidates found so far, with GWP values comparable to those of hydrocarbon (HC) based refrigerants.
Refrigerants are complex molecules and their blends are highly non-ideal mixtures. Understanding the phase behaviour and accurately predicting the thermophysical, interfacial and transport properties of these systems is essential for designing and evaluating refrigeration cycle performances and determining the optimal compositions [7,8]. Hence, the development of new refrigerants requires not only a low GWP, but also an accurate evaluation of their physicochemical properties to determine their capacity to substitute HFCs refrigerants without a loss of efficiency. As mentioned, HFOs represent a realistic alternative due to their excellent environmental properties, although its relative high flammability prevents their use as single compounds. Hence, current options consider the combination of HFCs or HCs with HFOs, forming azeotropic blends with similar properties but lower GWPs [9,10].
We will present and discuss here results obtained from a consistent thermodynamic model that characterizes new fourth-generation HFOs-based refrigerants with the SAFT approach , using the soft-SAFT  model compared with experimental data and with (Polar) PC-SAFT [9,10,13].
The soft-SAFT evaluation of the HFOs has been performed based on a molecular model transferred from HFCs, which had already been characterized in a previous work , taking advantage of the similarities between the two chemical structures. As a result, a set of optimized molecular parameters for these HFOs is provided, being consistent from a structural perspective. The description of the saturated density and vapor pressure is very accurate, in all cases, while the heat capacity and the speed of sound are predicted to validate the model, finding also very good agreement with the experimental information. Additionally, a very good description of the surface tension and the viscosity of these compounds is achieved by using the Density Gradient Theory and the Free-Volume theory coupled into soft-SAFT. Next, blends between HFCs and the two most common HFOs, R1234yd and R1234ze have been adequately described, providing a realistic picture of their phase equilibria, interfacial behavior and viscosity. The model can then be used for the prediction of any blend by varying the composition, as well as the behavior of ternary mixtures of refrigerants.
The work is completed with a process simulation of a cascade refrigeration system, where the common 3rd generation refrigerant R410 is compared with these new 4th generation mixtures. The thermodynamic information of the system is calculated using the soft-SAFT model and introduced in the process simulator Aspen Plus. A comparison of the Coefficient of Performance (CoP) is done for different cases, in order to establish the best alternative to R410.
This research is supported by Project KET4F-Gas â SOE2/P1/P0823 which is co-financed by the European Regional Development Fund within the framework of Interreg Sudoe programme. Additional partial support has been provided by Khalifa University of Science and Technology under project CIRA-2018-121.
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