6 citations · 8 across the 2 of their papers we have counts for
2 papers
cs.LG2023★ 2 cited
An unsupervised machine-learning-based shock sensor for high-order supersonic flow solvers
Andrés Mateo-Gabín, Kenza Tlales, Eusebio Valero +2
We present a novel unsupervised machine-learning sock sensor based on Gaussian Mixture Models (GMMs). The proposed GMM sensor demonstrates remarkable accuracy in detecting shocks a…
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…