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Communication Dans Un Congrès Année : 2022

A low-rank tensor method for parameterized linear fluid-structure interaction problems

Résumé

This talk will present a low-rank tensor method for parameterized linear fluid-structure interaction problems. In this work, the fluid is governed by the incompressible Stokes equations, and we assume a thick-walled solid model. In order to reduce the computational cost associated with the coupled problem, we develop a low-rank tensor method based on the low-rank Generalized Minimal Residual method. This one is then employed in an uncertainty quantification task to perform a large number of simulations. The preliminary results show the significant reduction of the computational cost provided by the proposed method.
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hal-04010551 , version 1 (01-03-2023)

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  • HAL Id : hal-04010551 , version 1

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Sébastien Riffaud, Miguel Angel Fernández, Damiano Lombardi. A low-rank tensor method for parameterized linear fluid-structure interaction problems. CMBE 2022 - 7th International Conference on Computational and Mathematical Biomedical Engineering, Jun 2022, Milan, Italy. ⟨hal-04010551⟩
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