/ White papers

How to Run 100 Ship Design Configurations in Less than 10 min with Extrality Deep Learning Physics

Antoine Reverberi
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Deep Learning Physics for the Hydrodynamics of Trading Vessels

Jonas Verrière
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How to Improve a Hull Form with Extrality Deep Learning Physics Platform

Antoine Reverberi
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/Extrality published papers

INFINITY: Neural Field Modeling for Reynolds-Averaged Navier-Stokes Equations
Louis Serrano, Leon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari
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Speed up Aerodynamic Optimization Thanks to Deep Learning Physics: Stellantis RAM Truck Example
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Multi-Objective Hull Form Optimization with CAD Engine-based Deep Learning Physics for 3D Flow Prediction
Jocelyn Ahmed Mazari, Antoine Reverberi, Pierre Yser, Sebastian Sigmund
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Deep Learning Physics for the Hydrodynamics of Trading Vessels
Jonas Verrière, Jocelyn Ahmed Mazari, Antoine Reverberi, Francis Hueber
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AirfoilRANS: High Fidelity Computational Fluid Dynamics Dataset for Approximating Reynolds-Averaged-Navier–Stokes Solutions
Florent Bonnet, Jocelyn Ahmed Mazari, Paola Cinnella, Patrick Gallinari
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An extensible Benchmarking Graph-Mesh dataset for studying Steady-State Incompressible Navier-Stokes Equations
Florent Bonnet, Jocelyn Ahmed Mazari, Thibaut Munzer, Pierre Yser, Patrick Gallinari
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Multi-scale Physical Representations for Approximating PDE Solutions with Graph Neural Operators
Léon Migus, Yuan Yin, Jocelyn Ahmed Mazari, Patrick Gallinari
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