Time-averaged steady vs. unsteady adjoint: a comparison for cases with mild unsteadiness

Hueckelheim, Jan; Xu, Shugen; Gugala, Mateusz; Müller, Jens-Dominik

doi:10.2514/6.2015-1953

Cited by 1 publication

(1 citation statement)

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“…We use an approach in which only the physical time steps are stored during the primal computation and restored during the adjoint computation, as presented in [9] and Algorithm 1. The memory requirements are orders of magnitude smaller compared to the brute-force method of storing every iteration.…”

Section: Physical Checkpointingmentioning

confidence: 99%

Checkpointing with Time Gaps for Unsteady Adjoint CFD

Hückelheim

Müller

2018

Computational Methods in Applied Sciences

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Gradient-based optimisation using adjoints is an increasingly common approach for industrial flow applications. For cases where the flow is largely unsteady however, the adjoint method is still not widely used, in particular because of its prohibitive computational cost and memory footprint. Several methods have been proposed to reduce the peak memory usage, such as checkpointing schemes or checkpoint compression, at the price of increasing the computational cost even further. We investigate incomplete checkpointing as an alternative, which reduces memory usage at almost no extra computational cost, but instead offers a trade-off between memory footprint and the fidelity of the model. The method works by storing only selected physical time steps and using interpolation to reconstruct time steps that have not been stored. We show that this is enough to compute sufficiently accurate adjoint sensitivities for many relevant cases, and does not add significantly to the computational cost. The method works for general cases and does not require to identify periodic cycles in the flow.

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Section: Physical Checkpointingmentioning

confidence: 99%