# alexpapados/Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics

<https://repo.masters-masters.com/repos/alexpapados/Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics>

[Accueil](https://repo.masters-masters.com/) › [alexpapados](https://repo.masters-masters.com/owners/alexpapados) › [Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics](https://repo.masters-masters.com/repos/alexpapados/Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics)

alexpapados/Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics, dépôt open source à 232 étoiles sur GitHub. Carte Prototype de RepoMasters.

| Champ | Valeur |
| --- | --- |
| Propriétaire | [alexpapados](https://repo.masters-masters.com/owners/alexpapados) |
| Étoiles | 232 |
| Forks | 50 |
| Langage | [Python](https://repo.masters-masters.com/languages/python) |
| Licence | Aucune |
| Création | 2021 |
| Sujets | pinns, computational-fluid-dynamics, computational-physics, physics-informed-neural-networks, physics-based-simulation, linear-elasticity, hydrodynamics, shock-tube |
| Rang | [Prototype (100 à 249 ★)](https://repo.masters-masters.com/ranks/rush) |
| Voir sur GitHub | [alexpapados/Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics](https://github.com/alexpapados/Physics-Informed-Deep-Learning-Solid-and-Fluid-Mechanics) |

## Fiche du dépôt

Using Physics-Informed Deep Learning (PIDL) techniques (W-PINNs-DE & W-PINNs) to solve forward and inverse hydrodynamic shock-tube problems and plane stress linear elasticity boundary value problems

Rang des dépôts qui ont 100 à 249 ★ sur GitHub. Probabilité publiée par carte tirée : 70 %. Rareté : Commune.

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Données : GitHub · Illustration dessinée par RepoMasters à partir de l’identifiant du dépôt et de la couleur de son langage.
