Parallel-in-time adjoint-based optimization – application to unsteady incompressible flows
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Embargo End Date:
2024-10-12
Type
ArticleKAUST Department
Department of Mechanical Engineering, KAUST, 23955 Thuwal, Saudi ArabiaMechanical Engineering Program
Physical Science and Engineering (PSE) Division
Date
2022-10-12Embargo End Date
2024-10-12Permanent link to this record
http://hdl.handle.net/10754/684308
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Gradient-based optimization algorithms, where gradient information is extracted using adjoint equations, are efficient but can quickly slow down when applied to unsteady and nonlinear flow problems. This is mainly due to the sequential nature of the algorithm, where the primal problem is first integrated forward in time, providing the initial condition for the adjoint problem, which is then integrated backward. In order to address the sequential nature of this optimization procedure parallel-in-time algorithms can be employed. However, the characteristics of the governing equations of interest in this work, and in particular, the divergence-free constraint (incompressibility effect) as well as the nonlinearity and the unsteadiness of the flow, make direct application of existing parallel-in-time algorithms less than straightforward. In this work, we introduce a parallel-in-time procedure, applied to the integration of the adjoint problem, which addresses all the existing constraints and allows quick access to local gradients. The performance of the proposed algorithm is assessed for both steady and unsteady actuation; in both cases it readily outperforms the sequential algorithm.Citation
Costanzo, S., Sayadi, T., Fosas de Pando, M., Schmid, P. J., & Frey, P. (2022). Parallel-in-time adjoint-based optimization – application to unsteady incompressible flows. Journal of Computational Physics, 471, 111664. https://doi.org/10.1016/j.jcp.2022.111664Sponsors
M.F.P. gratefully acknowledges financial support from MINECO/AEI and FEDER/UE through grant DPI2016-75777-R.Publisher
Elsevier BVJournal
Journal of Computational PhysicsAdditional Links
https://linkinghub.elsevier.com/retrieve/pii/S0021999122007276https://hal.archives-ouvertes.fr/hal-03852515/document
ae974a485f413a2113503eed53cd6c53
10.1016/j.jcp.2022.111664