From dfa5c61798545598c15bb3d585125cf708abfaeb Mon Sep 17 00:00:00 2001
From: Noels Ludovic <l.noels@uliege.be>
Date: Wed, 6 Dec 2023 17:12:57 +0000
Subject: [PATCH] Update README.md
---
SFEM/README.md | 72 +++++++++++---------------------------------------
1 file changed, 15 insertions(+), 57 deletions(-)
diff --git a/SFEM/README.md b/SFEM/README.md
index 100332f..6ddae10 100644
--- a/SFEM/README.md
+++ b/SFEM/README.md
@@ -1,4 +1,4 @@
-# sveResponses
+# Stochastic Finite Element Method (SFEM)
[](https://creativecommons.org/licenses/by/4.0/)
[](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
[](https://www.python.org/downloads/) [](https://github.com/pandas-dev/pandas) [](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:
--
GitLab