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This repository contains google colab based FEniCS implementation of the elastodynamics problem. This model will be further extended to include Physics Informed Neural Network (PINN) using Long Short-Term Memory (LSTM).
1. Prerequisites
We use python 3.6.9 as the programming language. In this project we use the libraries :
The domain is divided into $7$ non-overlapping subdomains: $\bar{\omega} = \bigcup\limits_{i=1}^{7} \bar{\omega}_{i}$. The balance of linear momentum in strong form for a given source term $\overrightarrow{b}$ is given by:
$$\rho \overrightarrow{\ddot{u}} = \nabla \cdot \overline{\overline{\sigma}} + \rho \overrightarrow{b} \ , \ \overrightarrow{\dot{u}} = \frac{\partial \overrightarrow{u}}{\partial t} \ , \ \overrightarrow{\ddot{u}} = \frac{\partial^2 \overrightarrow{u}}{\partial t^2} \ \text{in} \ \omega \times (0,\mathcal{T}] .$$
Above equation is solved using Finite Element Method in space and generalised-$\alpha$method in time to compute the displacement field $\overrightarrow{u}(x,t)$ at given point $x$ and time $t$. The material properties (Lam'e parameters $\lambda,\mu$ or Young modulus $E$ and Poisson ratio $\nu$) vary across each subdomain characterising different material constituting the subdomain, i.e.:
The damping term$c(\overrightarrow{\dot{u}},\overrightarrow{v})$ is chosen as linear combination of the mass matrix and the stiffness matrix (Rayleigh damping). The discrete form of the equation can be written as:
This code has been developed by [Nirav Shah] email.
6. How to cite
@misc{elastodynamics_LSTM_PINN,
key = {ElastodynamicsLSTMPINN},
author = {Shah, N.V.},
title = {{Long Short Term Memory based Physics Informed Neural Network for elastodynamics problem, Version 0.1}},
month = July,
url = {https://github.com/niravshah241/elastodynamics_LSTM_PINN.git},
year = 2022
}
7. License
FEniCS is freely available under the GNU LGPL, version 3.
Matplotlib only uses BSD compatible code, and its license is based on the PSF license. Non-BSD compatible licenses (e.g., LGPL) are acceptable in matplotlib toolkits.
Accordingly, this code is freely available under the GNU LGPL, version 3 and BSD-license.
8. Disclaimer
In downloading this SOFTWARE you are deemed to have read and agreed to the following terms: This SOFT- WARE has been designed with an exclusive focus on civil applications. It is not to be used for any illegal, deceptive, misleading or unethical purpose or in any military applications. This includes ANY APPLICATION WHERE THE USE OF THE SOFTWARE MAY RESULT IN DEATH, PERSONAL INJURY OR SEVERE PHYSICAL OR ENVIRONMENTAL DAMAGE. Any redistribution of the software must retain this disclaimer. BY INSTALLING, COPYING, OR OTHERWISE USING THE SOFTWARE, YOU AGREE TO THE TERMS ABOVE. IF YOU DO NOT AGREE TO THESE TERMS, DO NOT INSTALL OR USE THE SOFTWARE.
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This repository contains google colab based FEniCS implementation of the elastodynamics problem.