most citedMachine learning adaptation for laminar and turbulent flows: applications to high order discontinuous Galerkin solvers

6 citations · 9 across the 2 of their papers we have counts for

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2 papers

math.NA2022★ 3 cited

Truncation Error-Based Anisotropic -Adaptation for Unsteady Flows for High-Order Discontinuous Galerkin Methods

Andrés M. Rueda-Ramírez, Gerasimos Ntoukas, Gonzalo Rubio +2

In this work, we extend the -estimation method to unsteady problems and use it to adapt the polynomial degree for high-order discontinuous Galerkin simulations of unsteady flows…

physics.flu-dyn2022★ 6 cited

Machine learning adaptation for laminar and turbulent flows: applications to high order discontinuous Galerkin solvers

Kenza Tlales, Kheir-Eddine Otmani, Gerasimos Ntoukas +2

We present a machine learning-based mesh refinement technique for steady and unsteady flows. The clustering technique proposed by Otmani et al. arXiv:2207.02929 [physics.flu-dyn] i…