Multi-fidelity parametric sensitivity estimation for large eddy simulation with the Spalart–Allmaras model

A novel approach to compute affordable approximate sensitivities in a large-eddy simulation (LES) is proposed and assessed. The approach is based on solving a Reynolds-averaged Navier–Stokes (RANS) problem that has been linearized around the mean LES solution, with closure modeling required for the linearized changes in turbulent Reynolds stresses. In the present study, the closure modeling is based on a linearized algebraic turbulence model. The method is assessed for the flow over a NACA0012 airfoil at a fixed angle of attack, with the Reynolds number as the variable parameter. The results show that, provided an accurate linearized closure model, the method predicts the correct sensitivity of the skin friction coefficient and the mean velocity field at the cost of a linearized RANS, which provides an important proof-of-concept for this approach. The linearized algebraic turbulence model with standard model coefficients produces a reasonably accurate sensitivity, but the results also suggest that accuracy could be gained from recalibrating the model coefficients for this new use of the model.

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Multifidelity Approach to Sensitivity Estimation in Large-Eddy Simulation

Arias-Ramírez

Oberoi

Larsson

2023

AIAA Journal

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Multi-fidelity parametric sensitivity estimation for large eddy simulation with the Spalart–Allmaras model

Cited by 1 publication

References 24 publications

Multifidelity Approach to Sensitivity Estimation in Large-Eddy Simulation

Multifidelity Approach to Sensitivity Estimation in Large-Eddy Simulation

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