62 citations · 87 across the 8 of their papers we have counts for
8 papers
HORSES3D-GPU: A high-order discontinuous Galerkin solver for multi-GPU systems
Gerasimos Ntoukas, Gonzalo Rubio, Abbas Ballout +13
We present the GPU acceleration and large-scale performance assessment of HORSES3D, an open-source high-order discontinuous Galerkin solver for computational fluid dynamics. The so…
Can Explicit Subgrid Models Enhance Implicit LES Simulations? A Very High-Order Solver Perspective
Gonzalo Rubio, Gerasimos Ntoukas, Miguel Chávez-Módena +5
High-order discontinuous Galerkin (DG) methods offer excellent accuracy for turbulent-flow simulations and are increasingly attractive on GPU-oriented architectures, where high pol…
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…
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…
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…
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…
towards a robust detection of viscous and turbulent flow regions using unsupervised machine learning
Kheir-Eddine Otmani, Gerasimos Ntoukas, Esteban Ferrer
We propose an invariant feature space for the detection of viscous dominated and turbulent regions (i.e., boundary layers and wakes). The developed methodology uses the principal i…
HORSES3D: a high-order discontinuous Galerkin solver for flow simulations and multi-physics applications
E. Ferrer, G. Rubio, G. Ntoukas +10
We present the latest developments of our High-Order Spectral Element Solver (HORSES3D), an open source high-order discontinuous Galerkin framework, capable of solving a variety of…