Numerical study of transonic separation flow using an anisotropic turbulence model

A transonic turbulent separation flow in a converging-diverging transonic diffuser was studied, when there existed a separation bubble on the top wall of the diffuser triggered by strong shock-wave-boundary-layer-interaction (SWBLI). To capture the essential behavior of this complex flow, the current study utilized an anisotropic turbulence model developed on the basis of a statistical partial average scheme. The first order moment of turbulent fluctuations, retained by a novel average scheme, and the turbulent length scale, can be determined from the momentum equations and mechanical energy equation of the fluctuation flow, respectively. The two physical quantities were readily used to construct the nonlinear anisotropic eddy viscosity tensor and to significantly improve the computational results. Comparisons between the computational results and experimental data were carried out for velocity profiles, pressure distribution, skin friction coefficient, Reynolds stress as well as streamline vectors distribution. Without using any empirical coefficients and wall functions, the numerical results were in good agreement with the available experimental data, further confirming that the nonlinear anisotropic eddy viscosity tensor is the decisive factor for the success of the computational results.

Numerical study of transonic separation flow using an anisotropic turbulence model

A transonic turbulent separation flow in a converging-diverging transonic diffuser was studied, when there existed a separation bubble on the top wall of the diffuser triggered by strong shock-wave-boundary-layer-interaction (SWBLI). To capture the essential behavior of this complex flow, the current study utilized an anisotropic turbulence model developed on the basis of a statistical partial average scheme. The first order moment of turbulent fluctuations, retained by a novel average scheme, and the turbulent length scale, can be determined from the momentum equations and mechanical energy equation of the fluctuation flow, respectively. The two physical quantities were readily used to construct the nonlinear anisotropic eddy viscosity tensor and to significantly improve the computational results. Comparisons between the computational results and experimental data were carried out for velocity profiles, pressure distribution, skin friction coefficient, Reynolds stress as well as streamline vectors distribution. Without using any empirical coefficients and wall functions, the numerical results were in good agreement with the available experimental data, further confirming that the nonlinear anisotropic eddy viscosity tensor is the decisive factor for the success of the computational results.