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Discrete adjoint methodology for general multiphysics problems A modular and efficient algorithmic outline with implementation in an open-source simulation software
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DOI：10.1007/s00158-021-03117-5.png)
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This article presents a methodology whereby adjoint solutions for partitioned multiphysics problems can be computed efficiently, in a way that is completely independent of the underlying physical sub-problems, the associated numerical solution methods, and the number and type of couplings between them. By applying the reverse mode of algorithmic differentiation to each discipline, and by using a specialized recording strategy, diagonal and cross terms can be evaluated individually, thereby allowing different solution methods for the generic coupled problem (for example block-Jacobi or block-Gauss-Seidel). Based on an implementation in the open-source multiphysics simulation and design software SU2, we demonstrate how the same algorithm can be applied for shape sensitivity analysis on a heat exchanger (conjugate heat transfer), a deforming wing (fluid-structure interaction), and a cooled turbine blade where both effects are simultaneously taken into account.
Keyword:
Discrete adjoints
Multiphysics
Sensitivity analysis
Algorithmic differentiation
Fluid-structure interaction
Conjugate heat transfer
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4
论文数:
4.9K
被引数:
1.7W
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