A Physics-Informed Neural Network to solve 2D steady-state heat equation.
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Updated
May 31, 2024 - Jupyter Notebook
A Physics-Informed Neural Network to solve 2D steady-state heat equation.
Creating a function in MATLAB to 3D plot the transfer of heat over time by solving the one dimensional partial differential heat equation.
Repository for the Software and Computing for Applied Physics course at the Alma Mater Studiorum - Università di Bologna
Tutorials for MAM3040W Advanced Numerical Analysis
Sub-package of spatstat containing code for linear networks
A Maxima package to compute Fourier series and solve partial differential equations.
Here, we will provide a PyTorch regime to handle the partial differential equation solution of the heat equation by executing Deep Kolmogorov Method of Beck et. al.
Course material I created for the tutorial "Mathematical Modelling in Climate Research" at the Freie Universität Berlin
Applying the finite-difference method to the Convection Diffusion equation in python3. Examples included: One dimensional Heat equation, Transport equation, Fokker-Plank equation and some two dimensional examples.
A simple processor with a grid of cores that can only interact with their immediate neighbors
The following code runs a simulation of the heat diffusion equation for cylindrical coordinates
Heat diffusion, Turing patterns, Thermal dephasing
Numerical Methods
Numerical Method for Solving Basic PDE
Solution of 1D and 2D PDEs using Physics Informed Neural Networks (PINNs)
Two dimensional heat equation resolution with the help of the Finite Volume Method on a cartesian mesh
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