Enhancing robustness and accuracy of supercritical CO2 compressor performance prediction in closed Brayton cycles: A thermodynamic properties-based numerical method

The optimization of the closed Brayton cycle results in the inlet condition of supercritical CO2 (sCO2) compressors being near the critical point. However, this proximity leads to decreased robustness and accuracy during numerical simulations. To enhance computational fluid dynamics (CFD) robustness and accuracy, a method utilizing Cubic B-spline smoothing is proposed to reconstruct thermodynamic properties using property look-up tables (LUTs). After revealing the characteristics and action mechanism of sCO2 thermodynamic properties on the solver, effects of the method on solution robustness, accuracy, and the relationship with resolution are systematically investigated. The results demonstrate that this method effectively addresses the deficiencies arising from the inability of original LUTs to adapt to the high resolution and the presence of pseudo-convergence. The residuals achieve the convergence requirement in half the iteration steps compared to the original method, resulting in an over one-fold reduction in calculation time. The solution robustness is significantly enhanced by over tenfold, and the calculation accuracy is improved. This improvement increases the sensitivity of friction loss and secondary flow loss to drastic changes in thermodynamic properties. As a result, a highly robust and accurate performance prediction scheme for centrifugal compressor components is established.