Computer simulations were performed using ESyS-Particle and GenGeo software. The code was prepared using the materials available in the Tutorial: https://launchpadlibrarian.net/539636912/ESyS-Particle_Tutorial.pdf ESyS-Particle is Open Source software for particle-based numerical modelling. The software implements the Discrete Element Method (DEM), a widely used technique for modelling processes involving large deformations, granular flow and/or fragmentation. ESyS-Particle is designed for execution on parallel supercomputers, clusters or multi-core PCs running a Linux(or Windows)-based operating system. The C++ simulation engine implements spatial domain decomposition via the Message Passing Interface (MPI). A Python wrapper API provides flexibility in the design of numerical models, specification of modelling parameters and contact logic, and analysis of simulation data. Description, installation: https://launchpad.net/esys-particle GenGeo is a library of tools for creating complex particle geometries for use in ESyS-Particle simulations. GenGeo is a standalone application with a Python API that creates geometry files suitable for importing into ESyS-Particle simulations. The functionality of GenGeo far exceeds the in-simulation geometry creation utilities provided by ESyS-Particle itself. Description, installation: https://launchpad.net/esys-particle/gengeo Machine Learning Analysis was performed using Python 3 and its libraries - scikit-learn and others. SCHEDULE OF THE SIMULATIONS: 1) Create Dataset - Start of the simulation (start.py) Code to run a series of simulations with different parameters. Author: own implementation 2) Create Dataset - ESyS-Particle Main Simulation (shear.py) Main simulation code. Author: implementation based on Tutorial 3) Create Dataset - ESyS-Particle ServoWallLoader (ServoWallLoader.py) 4) Create Dataset - ESyS-Particle WallLoader (WallLoader.py) Two files that manage the movement of walls. Author: from Tutorial 5) Create Dataset - Macroscopic Friction Coefficient (bfc.py) Code to calculate Macroscopic Friction Coefficient Author: from Tutorial 6) Create Dataset - ESyS-Particle GenGeo Model (model.py) Code to create model geometry Author: implementation based on Tutorial 7) Create Dataset 2 - Current Particle Information (friction_dataset.py) Code to extract information about particles Author: own implementation 8) Machine Learning Analysis - Part 1 (friction_mlpart1.py) Application of Machine Learning Models to Dataset 1 Author: own implementation based on Python's libraries 9) Machine Learning Analysis - Part 2 (friction_mlpart2.py) Application of Machine Learning Models to Dataset 2 Author: own implementation based on Python's libraries