Bidar, O., He, P., Anderson, S. orcid.org/0000-0002-7452-5681 et al. (1 more author) (2022) An open-source adjoint-based field inversion tool for data-driven RANS modelling. In: AIAA AVIATION 2022 Forum. AIAA AVIATION 2022 Forum, 27 Jun - 01 Jul 2022, Chicago, IL, USA (and online). AIAA Aviation Forum Proceedings (2022). American Institute of Aeronautics and Astronautics
Abstract
This paper presents an open-source tool for using high-fidelity simulation or experimental data to improve steady-state Reynolds-averaged Navier--Stokes (RANS) turbulence models. The field inversion approach employed, involves perturbations of the production term in the model transport equation through a spatial field and the iterative optimisation of this field such that the error between model prediction and data is minimised. This highly dimensional inverse problem requires the adjoint method for efficient gradient-based optimisation. It has been successfully applied to reconstruct turbulent mean flows with limited data. However, the implementation is a high barrier to entry as the intrusive development process involves the CFD solver, the adjoint solutions, and the optimiser, making it a time-consuming and laborious task. In this work we integrate open-source codes to enable a flexible framework for field inversion application, open to all interested CFD practitioners. The software capabilities are demonstrated using three flow cases where traditional turbulence models (Spalart--Allmaras and Wilcox k-omega for this work) perform poorly due to flow separation and adverse pressure gradients. The data used include wind-tunnel experiments and direct numerical simulations, and field inversion scenarios considered integral (e.g. lift coefficient), surface (e.g. skin friction), and volume (e.g. velocity profiles) data, in order of decreasing sparsity.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2022 by Omid Bidar. Published by the American Institute of Aeronautics and Astronautics, Inc. This is an author-produced version of a paper subsequently published in AIAA AVIATION 2022 Forum. Uploaded in accordance with the publisher's self-archiving policy. |
Keywords: | Reynolds Averaged Navier Stokes; Spalart Allmaras Turbulence Model; Velocity Profiles; Skin Friction Coefficient; Lift Coefficient; Direct Numerical Simulation; Flow Separation; Inverse Problems; Wind Tunnels; C++ Programming Language |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield) |
Funding Information: | Funder Grant number Engineering and Physical Sciences Research Council n/a |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 08 Jul 2022 10:38 |
Last Modified: | 04 Aug 2022 10:50 |
Status: | Published |
Publisher: | American Institute of Aeronautics and Astronautics |
Series Name: | AIAA Aviation Forum Proceedings |
Refereed: | Yes |
Identification Number: | 10.2514/6.2022-4125 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:188728 |