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Physics-informed neural networks for inverse problems in supersonic flows
Accurate solutions to inverse supersonic compressible flow problems are often required for designing specialized aerospace vehicles.
Consistent and symmetry preserving data-driven interface reconstruction for the level-set method
We focus on interface reconstruction (IR) in the level-set method, i. e. the computation of the volume fraction and apertures.
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