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Automatic differentiation of a spectral difference code for sensitivity analysis

Cardesa, José I. and Airiau, Christophe Automatic differentiation of a spectral difference code for sensitivity analysis. (2019) In: 72nd Annual Meeting of the APS Division of Fluid Dynamics, 23 November 2019 - 26 November 2019 (Seattle, United States). (Unpublished)

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Abstract

The computational fluid dynamics code JAGUAR, developed jointly by ONERA (Toulouse) and CERFACS, is a high-order code based on spectral differences and intended for unsteady aerodynamic simulations. In order to extend its use for shape optimization and flow control, it is convenient to adapt the code so that computing flow sensitivities is an efficient yet flexible process that can be adapted to very different problems. For this reason, a fully discrete approach was chosen that relies on automatic differentiation. A test case was analyzed to validate our approach in an unsteady problem, allowing us to identify key modifications to be implemented on the code so as to streamline the differentiation process and ease its replication in other problems. Tangent and adjoint modes were used to differentiate the parallel version of the code with TAPENADE and the adjoinable MPI library. Execution times and coding strategies will be provided to illustrate the benefits and drawbacks of the different approaches.

Item Type:Conference or Workshop Item (Other)
Additional Information:No full-text document attached to this repository.
HAL Id:hal-02559278
Audience (conference):International conference without published proceedings
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Institution:French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE)
Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE)
Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE)
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Funders:
European Commission - Réseau thématique de recherche avancée Sciences et Technologies pour l'Aéronautique et l'Espace - RTRA STAE (FRANCE)
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Deposited On:30 Apr 2020 09:48

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