01 décembre 2022

Webinar Esteban Ferrer

Esteban Ferrer is a professor of applied mathematics at the School of Aeronautics (ETSIAE-UPM). He obtained his Ph.D. by the University of Oxford (UK) and has 20 years of industrial and academic experience in developing numerical techniques for fluid problems. He works actively with industry and coordinates the two EU projects. His main interests include high-order methods for fluid dynamics, turbulence modelling, machine learning, aeroacoustics for aeronautics and wind energy. He has written more than 90 journal and conference papers on these topics.
New avenues in high order fluid dynamics

Abstract: 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 flow applications, including compressible flows (with or without shocks), incompressible flows, various RANS and LES turbulence models, particle dynamics, multiphase flows, and aeroacoustics [1].
Recent developments allow us to simulate challenging multiphysics including turbulent flows, multiphase and moving bodies, using local p-adaption and fast multigrid time advancement. In addition, we present recent work that couples Machine Learning techniques and high order simulations.
[1] E Ferrer, G Rubio, G Ntoukas, W Laskowski, O Mario, S Colombo, A. Mateo-Gabn, F Manrique de Lara, D Huergo, J Manzanero, AM Rueda-Ramrez, DA Kopriva, E Valero. HORSES3D: a high order discontinuous Galerkin solver for flow simulations and multi-physic applications. arXiv:2206.09733, 2022

01 décembre 2022, 16h3017h30
Webinar (please contact J-P Laval or F. Romano for the link)

Next events

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Esteban Ferrer is a professor of applied mathematics at the School of Aeronautics (ETSIAE-UPM). He obtained his Ph.D. by the University of Oxford (UK) and has 20 years of industrial and academic experience in developing numerical techniques for fluid problems. He works actively with industry and coordinates the two EU projects. His main interests include high-order methods for fluid dynamics, turbulence modelling, machine learning, aeroacoustics for aeronautics and wind energy. He has written more than 90 journal and conference papers on these topics.