activity
20172026
most citedImproving aircraft performance using machine learning: a review

194 citations · 450 across the 19 of their papers we have counts for

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Showing physics.flu-dynShow all

6 papers · 1 filter

physics.flu-dyn2026

Mesh Adaptation on Hybrid Unstructured Meshes for Immersed Boundary Methods

Jonatan Núñez-de la Rosa, Esteban Ferrer, Eusebio Valero

In this work, we describe a new preprocessing tool for mesh adaptation on hybrid unstructured meshes with a target application on immersed boundary methods. The tool has as input a…

physics.flu-dyn2023★ 3 cited

A combined volume penalization / selective frequency damping approach for immersed boundary methods: application to moving geometries

Jiaqing Kou, Esteban Ferrer

This work extends, to moving geometries, the immersed boundary method based on volume penalization and selective frequency damping approach [J. Kou, E. Ferrer, A combined volume pe…

physics.flu-dyn2022★ 3 cited

Aeroacoustic airfoil shape optimization enhanced by autoencoders

Jiaqing Kou, Laura Botero-Bolívar, Román Ballano +4

We present a framework for airfoil shape optimization to reduce the trailing edge noise for the design of wind turbine blades. Far-field noise is evaluated using Amiet's theory cou…

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…

physics.flu-dyn2022★ 22 cited

Accelerating high order discontinuous Galerkin solvers using neural networks: 3D compressible Navier-Stokes equations

Fernando Manrique de Lara, Esteban Ferrer

We propose to accelerate a high order discontinuous Galerkin solver using neural networks. We include a corrective forcing to a low polynomial order simulation to enhance its accur…

physics.flu-dyn2022★ 14 cited

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…