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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