Session: 34-06 Geometry and fluid-structure interaction

Paper Number: 153540

Examining the Potential of High-Order SRS to Support RANS-Based Compressor Airfoil Optimization 

Turbomachinery aerodynamic optimizations are predominantly carried out using RANS-based CFD, reaching a high level of maturity over the past years through extensive practical experience. With ever increasing demands on designs, also the demands on simulation accuracy are increasing and efforts are being made to include scale resolving simulations (SRS) into the design process of turbomachinery. Although SRS are still too costly to be used as the primary simulation tool for optimization purposes in an industrial environment, they are on the verge of being included in optimization procedures.
This is supported by design trends such as turbo engine designs with smaller core engines, resulting in locally reduced Reynolds numbers. On the one hand, potential boundary layer separation and a high level of unsteadiness in these low Reynolds number flows amplify the uncertainties of RANS. On the other hand, the computational requirements of SRS are drastically reduced due to the reduced bandwidth of turbulent scales.

In order to assess the potential of utilizing SRS in optimization frameworks, previously optimized airfoils are re-evaluated with Large-Eddy Simulations (LES) based on a high-order Discontinuous Galerkin solver. First, a RANS-based optimization is performed for a low Reynolds number OGV airfoil with the aim of reducing the loss at the design point and an increased operating range. A carefully selected subset of Pareto-Front geometries is then re-simulated using LES to assess the impact of the chosen CFD methodology on the optimization result along the Pareto-Front.

It is analyzed how the performance of the surrogate models can be improved with  only few high-fidelity SRS solutions. Moreover, detailed flow analyses give insights on the deficiencies of RANS. 

The results indicate how optimizations can be driven into a suboptimal direction when relying solely on RANS, underscoring the necessity of incorporating SRS into the process chain and providing initial insights into how this can be done efficiently.

Presenting Author: Georgios Goinis German Aerospace Center (DLR)

Presenting Author Biography: Since 2009 at DLR

Authors:

Georgios Goinis German Aerospace Center (DLR)
Sutharsan Satcunanathan German Aerospace Center (DLR)
Michael Bergmann German Aerospace Center (DLR)