Deep Learning Applied to Physics and fluids

Deep Learning Applied to Physics and Fluids

Numerical simulations have been used for years to understand the behavior of physical systems; how the fluids interact with a structure, how a geometry is deformed under stress, or even the thermal distribution under heating conditions. Applied in the more diverse domains such as aero spatial, automobile, energy, etc., those calculations allow dimensioning prototypes and ensuring safe processes without having to build them. Notwithstanding, they can be computationally expensive and take many hours, …

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