(partial, unofficial) JAX-implementation for "Physics-informed Neural Networks for shell structures".
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Updated
Jul 15, 2024 - Python
(partial, unofficial) JAX-implementation for "Physics-informed Neural Networks for shell structures".
Simple implementation of finite element method
CalculiX examples by Prof. Martin Kraska from Brandenburg University of Applied Sciences. Excellent starting point to master parametric modelling with CGX and CCX.
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
Code TMA4900 Industrial Mathematics, Master’s Thesis
Code for building a reduced-order model for the linear elasticity equation on a square in 2D for my specialization Project at NTNU.
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