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# sveResponses
# Stochastic Finite Element Method (SFEM)
[![License: CC BY 4.0](https://img.shields.io/badge/License-CC_BY_4.0-lightgrey.svg)](https://creativecommons.org/licenses/by/4.0/)
[![MOAMMM](https://img.shields.io/badge/MOAMMM-2ea44f?logo=gitlab)](https://gitlab.uliege.be/moammm/moammmPublic)
......@@ -11,19 +11,21 @@ This repository contains:
## Table of Contents
1. [Spectral Generator of RF](#spectral-generator)
2. [RF vizualization](#rf-vizualization)
3. [Test Cases of MC SFEM](#mc-sfem)
1. [Dependencies and Prerequisites](#dependencies-and-prerequisites)
2. [Structure of Repository](#structure-of-repository)
3. [Spectral Generator of RF](#spectral-generator-of-rf)
4. [RF vizualization](#rf-vizualization)
5. [Test Cases of MC SFEM](#test-cases of-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) [![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.
* Python, pandas, matplotlib, texttabble and latextable are pre requisites for visualizing and navigating the data.
For generating mesh and for vizualization, gmsh (www.gmsh.info) is required.
* For generating mesh and for vizualization, gmsh (www.gmsh.info) is required.
For running simulations, cm3Libraries (www.ltas-cm3L) is required.
* For running simulations, cm3Libraries (http://www.ltas-cm3.ulg.ac.be/openSource.htm) is required.
### Instructions using apt & pip3 package manager
......@@ -41,49 +43,19 @@ Instructions for Debian/Ubuntu based workstations are as follows.
pip3 install matplotlib texttable latextable
```
### Pytorch
``` bash
pip3 install --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
```
### Lattice libraries
Build lattice libraries using the script:
``` bash
Scripts/LatticeLib/compile.sh
```
This creates lattice libraries inside `$HOME/.local/lib/moammmLattice`.
To use, append this into PYHONPATH by adding the following line in your .bashrc
``` bash
export PYTHONPATH=$PYTHONPATH:$HOME/.local/lib/moammmLattice
```
## Structure of Repository
[Scripts](./Scripts) contains all the code and libraries alongside the driver routine [driver.py](./Scripts/driver.py)
Data for SVEs is stored as DataPaths and LoadPaths, Surrogate models are stored as RNNSurrogate, under their respective lattice names as [Cell3](./Cell3/) and [Cell6](./Cell6).
Data is further organised into subfolders using a unique naming scheme based on their parameters.
* [generateRF](./generateRF) contains all the scripts used to generate and vizualize the random fields
* [cellRF](./cellRF) contains an example in which we generate a single variable random field on a lattice unit cell
* [rnnRF](./rnnRF) contains an example in which we generate a correlated two-variable random field and the siulations script to run Monte Carlo simulations on a multiscale lattice compression using a [MOAMMM stochastic neural network](https://gitlab.uliege.be/moammm/moammmPublic/syntheticdata/sveresponses) as surrogate of the cell response.
To understand the unique naming scheme we introduce the parameters next.
## Data Parameters
### generateRF
All parameters for data generation are defined inside driver routine [driver.py](./Scripts/driver.py), categorized as:
### Lattice Selection
| Parameter | Type | Description |
|:----------|:--------------:|:-------------------------------------------------------|
| cellType | String literal | Lattice identified by its numeric code: "3", "6", "9". |
### Load Path Parameters
### cellRF
Loading paths are generated for three types of loadings:
......@@ -91,21 +63,7 @@ Loading paths are generated for three types of loadings:
2. Random Cyclic paths with rate variant data points (CR).
3. Random Cyclic paths with constant rate data points (CC).
| Parameter | Type | Description |
|:-----------|:---------------:|:--------------------------------------------------------------------------------------|
| load_type | List of strings | Type of load Path: 'RW', 'CR', 'CC'. |
| r_max | Float | Upper bound of Right Cauchy Green (RCG) stretch Tensor norm $\bm{U}$. |
| eval_step | List of floats | Bounds for RCG tensor increment. |
| s_rate | List of floats | Bounds for strain rate. |
| k | Int | Number of paths for each load_type. |
| n_max | Int | Maximum allowable data points in a load path. |
| n_plot | Int | Number of paths for visualization in the plots. |
| n_split | Int | Number of collection bins (threads) - see [Thread creation](#thread-creation). |
| G_max | Float | Upper Bound for gradient of deformation gradient $\bm{G}$ - (Only for HO kinematics). |
| Geval_step | List of floats | Bounds for G increment - (Only for HO kinematics). |
### Lattice Geometry Parameters
### rnnRF
Random SVEs are generated for a selected lattice by varying either,the **strut radius** or the **volume fraction**. Geometrical parameters for lattices along with their description are as:
......
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