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Gaussian Process for Aerodynamic Pressures Prediction in Fast Fluid Structure Interaction Simulations

Abstract : The interaction between inertial, elastic and aerodynamic forces for structures subjected to a fluid flow may cause unstable coupled vibrations that can endanger the structure itself. Predicting these interactions is a time consuming but crucial task in an aircraft design process. In order to reduce the computational time surrogate reduced order models can be used in both structural and aerodynamic models. More over it is possible to avoid launching CFD computations at every time step. A database of aerodynamic pressure distribution on the structural component can be created conveniently sampling the space of the structural model DoF. Starting from the knowledge of the precomputed data-set a Gaussian Process can be applied to predict the pressure distribution on an unexplored point of the space of DoF. The knowledge of the standard deviation can be used to give indications on where to launch further CFD computations to enrich the database. This technique will be first applied to a database of pressures obtained using the software Xfoil®, later it will be applied to CFD simulations of type RANS launched with elsA® on one Flap track Fairing of an Airbus aircraft.
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Submitted on : Tuesday, July 3, 2018 - 1:06:38 PM
Last modification on : Thursday, February 27, 2020 - 1:17:39 AM
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  • HAL Id : hal-01828716, version 1
  • OATAO : 18004

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Ankit Chiplunkar, Elisa Bosco, Joseph Morlier. Gaussian Process for Aerodynamic Pressures Prediction in Fast Fluid Structure Interaction Simulations. 12th World Congress on Structural and Multidisciplinary Optimization, Jun 2017, Braunschweig, Germany. pp.221-233. ⟨hal-01828716⟩

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