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PINN

PINNs for solving multiphase poroelasticity relations

Fri, 2021-10-08 16:40 - haghighat

physics-informed neural networks

Link to the paper - PINN-Poroelasticity

If you are interested in physics informed neural networks (PINNs) and coupled single and multiphase flow in porous media, please check out our work below:

- We find it challenging to solve coupled poroelasticity relations using PINNs (data-free).

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Exact imposition of boundary conditions in physics-informed neural networks

Fri, 2021-04-30 23:41 - N. Sukumar

meshfree methods

We recently proposed a method that uses distance fields to exactly impose boundary conditions in physics-informed neural networks (PINN). This contribution is available as an arXiv preprint.

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SciANN: Scientific computations and physics-informed deep learning using artificial neural networks

Mon, 2020-05-25 12:10 - haghighat

neural networks

physics-informed

Interested in deep learning, scientific computations, solution, and inversion methods for PDE?

Check out the preprint at:

https://www.researchgate.net/publication/341478559_SciANN_A_Keras_wrappe...

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