A coupled adjoint method for optimal design in fluid-structure interaction problems with large displacements
File(s)
Author(s)
Sanchez Fernandez, Ruben
Type
Thesis
Abstract
Computational Fluid-Structure Interaction (FSI) methods have reached a significant level of maturity which has led to their incorporation into the analysis stage of industrial applications. However, optimising the structural and/or the aerodynamic performance in highly non-linear coupled FSI problems remains a challenging task, due to the high computational cost of evaluating the functions in this problem and their gradients. Adjoint methods have shown to be an
efficient methodology for this latter task, as they can compute sensitivities with a computational cost independent of the number of design variables. On the other hand, their implementation is complex, particularly when the linearisation of the system equations is convoluted.
In this thesis, we develop a novel technique for the evaluation of the coupled adjoint problem. It is based on the consistent application of Algorithmic Differentiation to the fixed-point iterators of the subproblems. This approach makes the computation of the adjoint independent from the solution methods employed for the primal problem, and overcomes the usual limitation for most realistic applications, which is the need for an explicit construction of the analytic Jacobian of the coupled problem. The method poses no restrictions to the non-linearity of the physics in
either the fluid or structural field, and it is amenable to partitioned solution methods for the adjoint equations.
We have implemented this method in the open-source SU2 suite, by incorporating structural analysis and FSI capabilities and combining them with the available AD tool for the solution of the coupled adjoint. Finally, the validity of the implementations is assessed through a number of studies. We test the structural and FSI solvers using commercial codes and benchmark cases. Then, we demonstrate the accuracy of the sensitivities obtained using the proposed method. The advantages of our adjoint method for gradient-based optimisation are finally shown for a range of cases, from structural-only to fully coupled optimal design problems.
efficient methodology for this latter task, as they can compute sensitivities with a computational cost independent of the number of design variables. On the other hand, their implementation is complex, particularly when the linearisation of the system equations is convoluted.
In this thesis, we develop a novel technique for the evaluation of the coupled adjoint problem. It is based on the consistent application of Algorithmic Differentiation to the fixed-point iterators of the subproblems. This approach makes the computation of the adjoint independent from the solution methods employed for the primal problem, and overcomes the usual limitation for most realistic applications, which is the need for an explicit construction of the analytic Jacobian of the coupled problem. The method poses no restrictions to the non-linearity of the physics in
either the fluid or structural field, and it is amenable to partitioned solution methods for the adjoint equations.
We have implemented this method in the open-source SU2 suite, by incorporating structural analysis and FSI capabilities and combining them with the available AD tool for the solution of the coupled adjoint. Finally, the validity of the implementations is assessed through a number of studies. We test the structural and FSI solvers using commercial codes and benchmark cases. Then, we demonstrate the accuracy of the sensitivities obtained using the proposed method. The advantages of our adjoint method for gradient-based optimisation are finally shown for a range of cases, from structural-only to fully coupled optimal design problems.
Version
Open Access
Date Issued
2017-09
Date Awarded
2018-03
Copyright Statement
Attribution NoDerivatives 4.0 International Licence (CC BY-ND)
Advisor
Palacios, Rafael
Sponsor
Engineering and Physical Sciences Research Council
United States. Air Force. European Office of Aerospace Research and Development
Grant Number
EP/J002070/1
Publisher Department
Aeronautics
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)