10 citations · 27 across the 6 of their papers we have counts for
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physics.flu-dyn2023★ 6 cited
Physically constrained eigenspace perturbation for turbulence model uncertainty estimation
Marcel Matha, Christian Morsbach
Aerospace design is increasingly incorporating Design Under Uncertainty based approaches to lead to more robust and reliable optimal designs. These approaches require dependable es…
physics.flu-dyn2022★ 2 cited
Applicability of machine learning in uncertainty quantification of turbulence models
Marcel Matha, Karsten Kucharczyk
White paper: The aim of this work is to apply and analyze machine learning methods for uncertainty quantification of turbulence models. In this work we investigate the classical an…