Optimization of two-phase R600a ejector geometries using a non-equilibrium CFD model

A vapor compression cycle, which is typically utilized for the heat pump, air conditioning and refrigeration systems, has inherent thermodynamic losses associated with expansion and compression processes. To minimize these losses and improve the energy efficiency of the vapor compression cycle, an ejector can be applied. However, due to the occurrence of complex physics i.e., non-equilibrium flashing compressible flow in the nozzle with possible shock interactions, it has not been feasible to model or optimize the design of a two-phase ejector. In this study, a homogeneous, non-equilibrium, two-phase flow computational fluid dynamics (CFD) model in a commercial code is used with an in-house empirical correlation for the mass transfer coefficient and real gas properties to perform a geometric optimization of a two-phase ejector. The model is first validated with experimental data of an ejector with R600a as the working fluid. After that, the design parameters of the ejector are optimized using multi-objective genetic algorithm (MOGA) based online approximation-assisted optimization (OAAO) approaches to find the maximum performance.