2 citations · 5 across the 5 of their papers we have counts for
5 papers
Reinforcement learning for anisotropic p-adaptation and error estimation in high-order solvers
David Huergo, Martín de Frutos, Eduardo Jané +3
We present a novel approach to automate and optimize anisotropic p-adaptation in high-order h/p solvers using Reinforcement Learning (RL). The dynamic RL adaptation uses the evolvi…
Accelerating high order discontinuous Galerkin solvers through a clustering-based viscous/turbulent-inviscid domain decomposition
Kheir-Eddine Otmani, Andrés Mateo-Gabín, Gonzalo Rubio +1
We explore the unsupervised clustering technique introduced in [25] to identify viscous/turbulent from inviscid regions in incompressible flows. The separation of regions allows so…
A comparative study of explicit and implicit Large Eddy Simulations using a high-order discontinuous Galerkin solver: application to a Formula 1 front wing
Gerasimos Ntoukas, Gonzalo Rubio, Oscar Marino +4
This paper explores two Large Eddy Simulation (LES) approaches within the framework of the high-order discontinuous Galerkin solver, Horses3D. The investigation focuses on an Inver…
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…
Numerical and experimental study of open-cell foams for the characterization of heat exchangers
Aitor Amatriain, Corrado Gargiulo, Gonzalo Rubio
A multiscale model of open-cell foams is developed for the characterization of heat exchangers. The model is applicable to a wide range of materials, cell sizes, and porosities. Th…