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Commit 0c114258 authored by noels's avatar noels
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This repository contains:
* Data generated by simulation of synthetic volume elements (SVE) constructed using lattices under investigation in MOAMMM project.
* Code to visualize and generate further SVE data.
* Recurrent Neural Network (RNN) based surrogate models, trained on the SVE data.
* Code to train surrogate model and visualize its predictions against the testing data.
* A spectral generator of random fields (RF).
* Scripts to vizualize of the random fields.
* 2 test cases of Monte-Carlo (MC) stochastic finite element simulations (SFEM).
## Table of Contents
1. [Dependencies and Prerequisites](#dependencies-and-prerequisites)
2. [Structure of Repository](#structure-of-repository)
3. [Data Parameters](#data-parameters)
4. [Data Generation](#data-generation)
5. [Database and Visualization](#database-and-visualization)
6. [Surrogate Training](#surrogate-modelling)
7. [Surrogate Testing](#surrogate-testing)
1. [Spectral Generator of RF](#spectral-generator)
2. [RF vizualization](#rf-vizualization)
3. [Test Cases of MC SFEM](#mc-sfem)
## Dependencies and Prerequisites
[![python - >=3.11](https://img.shields.io/badge/python->=3.11-2ea44f?logo=python)](https://www.python.org/downloads/) [![pandas - >=1.5.3](https://img.shields.io/badge/pandas->=1.5.3-2ea44f?logo=pandas)](https://github.com/pandas-dev/pandas) [![PyTorch - >=2.10](https://img.shields.io/badge/PyTorch->=2.10-2ea44f?logo=pytorch)](https://pytorch.org/get-started/locally/#linux-pip) [![matplotlib - >-3.5.2](https://img.shields.io/badge/matplotlib->--3.5.2-2ea44f)](https://matplotlib.org/)
[![python - >=3.11](https://img.shields.io/badge/python->=3.11-2ea44f?logo=python)](https://www.python.org/downloads/) [![pandas - >=1.5.3](https://img.shields.io/badge/pandas->=1.5.3-2ea44f?logo=pandas)](https://github.com/pandas-dev/pandas) [![matplotlib - >-3.5.2](https://img.shields.io/badge/matplotlib->--3.5.2-2ea44f)](https://matplotlib.org/)
Python, pandas, matplotlib, texttabble and latextable are pre requisites for visualizing and navigating the data.
For data generation and training / testing surrogate model, Pytorch and lattice libraries are required.
For generating mesh and for vizualization, gmsh (www.gmsh.info) is required.
For running simulations, cm3Libraries (www.ltas-cm3L) is required.
### Instructions using apt & pip3 package manager
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