Strongly-coupled fluid-structure interaction of lightweight membranes and shells
ORAL
Abstract
Numerical fluid-structure interaction simulations of lightweight, flexible structures, such as membranes and shells, are notoriously tricky due to the large deformations and the significant added-mass effect. These effects generate a very strongly coupled problem that requires implicit coupling algorithms to solve them or, in extreme cases, prevent reaching a stable solution altogether.
We discuss the numerical challenges of coupling a lightweight, flexible structure to an incompressible flow with two typical problems, an inverted flag undergoing limit-cycle flapping and a fluttering membrane wing. We compare different coupling approaches to a quasi-Newton scheme that constructs a least-square approximation of this Jacobian from input/output pairs of the previously converged time steps. We show that the quasi-Newton scheme performs well under mild added-mass effects. Convergence is heavily penalized when the added-mass effects are strong, preventing reasonable solution time. We apply these methods to lightweight membrane flutter and demonstrate the influence of unsteady fluid-structure interaction on coupling efficiency. Finally, we investigate using pre-trained machine learning approximations to the coupling Jacobian to speed up strongly coupled fluid-structure interaction simulations.
We discuss the numerical challenges of coupling a lightweight, flexible structure to an incompressible flow with two typical problems, an inverted flag undergoing limit-cycle flapping and a fluttering membrane wing. We compare different coupling approaches to a quasi-Newton scheme that constructs a least-square approximation of this Jacobian from input/output pairs of the previously converged time steps. We show that the quasi-Newton scheme performs well under mild added-mass effects. Convergence is heavily penalized when the added-mass effects are strong, preventing reasonable solution time. We apply these methods to lightweight membrane flutter and demonstrate the influence of unsteady fluid-structure interaction on coupling efficiency. Finally, we investigate using pre-trained machine learning approximations to the coupling Jacobian to speed up strongly coupled fluid-structure interaction simulations.
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Publication: 10.1016/j.jcp.2022.111076
Presenters
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Marin Lauber
TU Delft
Authors
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Marin Lauber
TU Delft
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Gabriel D Weymouth
TU Delft
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Georges Limbert
University of Southampton