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Robijns, Michel (author)
This thesis is part of a greater effort to use machine learning for the development of flexible and universal unresolved-scale models in large eddy simulation (LES). The novelty in the current work is that a neural network learns to predict the integral forms of the unresolved-scale terms directly without a priori assumptions on the underlying...
master thesis 2019
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van Korlaar, Arent (author)
Turbulence closure models will continue to be necessary in order to perform computationally affordable simulations in the foreseeable future. It is expected that Reynolds-averaged Navier-Stokes (RANS) turbulence models will still be useful with the further development of the more accurate, but computationally expensive large eddy simulation (LES...
master thesis 2019