ShotaDeguchi/PINN_Torch
Implementation of PINNs in PyTorch
This tool helps computational scientists and engineers find solutions to complex physics problems described by differential equations, like fluid dynamics or heat transfer. You input the governing equations and boundary conditions, and it outputs a highly accurate solution for the system's behavior. It's designed for researchers and practitioners in fields requiring numerical solutions to PDEs without extensive traditional numerical solver expertise.
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Use this if you need to solve partial differential equations (PDEs) by embedding physical laws directly into a neural network, especially for problems where traditional numerical methods are complex or data is scarce.
Not ideal if you are looking for a general-purpose machine learning framework for image recognition or natural language processing, or if you prefer established finite element/difference methods.
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Language
Python
License
MIT
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Last pushed
Apr 09, 2023
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