Predictions of flow distortions inside a serpentine diffuser from large-eddy simulations

TL;DR

This study uses large-eddy simulations to analyze flow separation and pressure distortions in a serpentine diffuser at various Mach numbers, achieving high accuracy in pressure recovery predictions and revealing non-local effects on flow separation.

Contribution

It demonstrates the effectiveness of advanced wall-modeled LES with dynamic tensor-coefficient Smagorinsky models in predicting flow distortions in complex diffuser geometries at different Mach regimes.

Findings

LES accurately predicts pressure recovery within 0.3%

LES captures azimuthal flow distortion within 7%

Simulations underestimate maximum azimuthal distortion and extreme events

Abstract

This work examines the flow separation and the resulting pressure distortions at the exit plane of a serpentine diffuser operating at both subsonic and transonic conditions. Wallmodeled large-eddy simulations (WMLES) using the charLES flow solver are performed at three exit-plane Mach numbers, Ma_AIP ~ {0.36, 0.46, 0.54}. First, it is shown that the onset of flow separation inside a serpentine diffuser may likely experience strong, non-local history effects. A grid refinement study consisting of five grids (from 30 million to 3 billion cells) is conducted for all Mach numbers. The recently proposed dynamic tensor-coefficient Smagorinsky subgrid-scale and sensor-aided non-equilibrium wall models compare favorably with experimental measurements for the pressure recovery and azimuthal flow distortion at all Mach numbers. The pressure recovery and azimuthal flow distortion are predicted to within 0.3% and 7%, respectively, which are both within the experimental error bounds. However, the simulations underpredict the maximum azimuthal distortion in comparison to the experiments for all conditions. Statistical comparisons of the dynamic azimuthal flow distortions suggest that the present LES reasonably captures the ring-averaged mean distortions, and the statistical distributions of the distortion around the mean. Extreme events are underestimated by the present simulations, potentially highlighting that significantly longer integration times may be necessary.