works on

From the 1 of 6 linked papers with an AI index.

activity
20242026
collaborators

6 papers

math.NA2026

HORSES3D-GPU: A high-order discontinuous Galerkin solver for multi-GPU systems

Gerasimos Ntoukas, Gonzalo Rubio, Abbas Ballout +13

The paper describes the GPU-accelerated version of the open-source high-order discontinuous Galerkin CFD solver HORSES3D, showing its performance and scalability on multi‑GPU syste…

math.NA2025

Optimal solutions employing an algebraic Variational Multiscale approach Part II: Application to Navier-Stokes

Suyash Shrestha, Marc Gerritsma, Gonzalo Rubio +2

This work presents a non-linear extension of the high-order discretisation framework based on the Variational Multiscale (VMS) method previously introduced for steady linear proble…

math.NA2025

Acoustic Propagation/Refraction Through Diffuse Interface Models

Abbas Ballout, Oscar A. Marino, Gerasimos Ntoukas +2

We present a novel approach for simulating acoustic (pressure) wave propagation across different media separated by a diffuse interface through the use of a weak compressibility fo…

math.NA2025

Optimal solutions employing an algebraic Variational Multiscale approach Part I: Steady Linear Problems

Suyash Shrestha, Marc Gerritsma, Gonzalo Rubio +2

This work extends our previous study from S. Shrestha et al. (2024) by introducing a new abstract framework for Variational Multiscale (VMS) methods at the discrete level. We intro…

physics.flu-dyn2024

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…

cs.LG2024

A reinforcement learning strategy to automate and accelerate h/p-multigrid solvers

David Huergo, Laura Alonso, Saumitra Joshi +3

We explore a reinforcement learning strategy to automate and accelerate h/p-multigrid methods in high-order solvers. Multigrid methods are very efficient but require fine-tuning of…