314arhaam/heat-pinn
A Physics-Informed Neural Network to solve 2D steady-state heat equations.
This project helps engineers and researchers model how heat distributes across a 2D surface. You input boundary conditions for temperature (e.g., specific temperatures at edges), and it outputs a prediction of the temperature across the entire area. It's designed for professionals in thermal engineering, materials science, or physics who need to understand heat transfer without complex experimental setups or traditional numerical methods.
172 stars. No commits in the last 6 months.
Use this if you need to quickly and accurately simulate steady-state heat distribution in 2D geometries, especially when traditional methods might be too slow or complex.
Not ideal if you require simulations for transient (time-dependent) heat transfer or highly complex 3D geometries, as this focuses on 2D steady-state problems.
Stars
172
Forks
23
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Aug 31, 2025
Commits (30d)
0
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