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Articles

A partitioned scheme for adjoint shape sensitivity analysis of fluid–structure interactions involving non-matching meshes

, , , , &
Pages 546-576 | Received 02 Jan 2020, Accepted 03 Aug 2020, Published online: 17 Aug 2020
 

Abstract

This work presents a partitioned solution procedure to compute shape gradients in fluid–structure interaction (FSI) using black-box adjoint solvers. Special attention is paid to project the gradients onto the undeformed configuration due to the mixed Lagrangian–Eulerian formulation of large-deformation FSI in this work. The adjoint FSI problem is partitioned as an assembly of well-known adjoint fluid and structural problems. The sub-adjoint problems are coupled with each other by augmenting the target functions with auxiliary functions, independent of the concrete choice of the underlying adjoint formulations. The auxiliary functions are linear force-based or displacement-based functionals which are readily available in well-established single-disciplinary adjoint solvers. Adjoint structural displacements, adjoint fluid displacements, and domain-based adjoint sensitivities of the fluid are the coupling fields to be exchanged between the adjoint solvers. A reduced formulation is also derived for the case of boundary-based adjoint shape sensitivity analysis for fluids. Numerical studies show that the complete formulation computes accurate shape gradients whereas inaccuracies appear in the reduced gradients. Mapping techniques including nearest element interpolation and the mortar method are studied in computational adjoint FSI. It is numerically shown that the mortar method does not introduce spurious oscillations in primal and sensitivity fields along non-matching interfaces.

Acknowledgments

The authors gratefully acknowledge the support of the International Graduate School of Science and Engineering (IGSSE) of the Technische Universität München, Germany, under project 9.10.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by International Graduate School of Science and Engineering of the Technische Universität München [9.10].

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