MINEDW Tutorial (Part 1: Menu Options)

In this tutorial we will briefly cover the MINEDW user interface, its components, and the MINEDW Menu with the different options and tools it provides to build numerical models.

Generate a Hybrid Mesh by Combining Block Ranger and GVol

This tutorial will demonstrate a method to create a hybrid mesh of tetrahedral zones to model the rock mass and hexahedral zones to model a concrete liner. Hexahedral zones for the liner are preferred in order to more accurately capture plastic strains in this region. The meshing is done by utilizing the Itasca Griddle volume mesher plug-in for Rhino 3D. Importing the final mesh into FLAC3D, for future finite volume modeling, is also demonstrated.

Using Python in FLAC3D 6

The Python programming language is embedded inside FLAC3D 6 and extended to allow FLAC3D models to be manipulated from Python programs. This webinar recording provides a brief introduction to Python scripting and includes many examples of using Python with FLAC3D.

Elastic Properties of Fractured Rock Masses With Frictional Properties and Power Law Fracture Size Distributions

We derive the relationships that link the general elastic properties of rock masses to the geometrical properties of fracture networks, with a special emphasis to the case of frictional crack surfaces.

We extend the well-known elastic solutions for free-slipping cracks to fractures whose plane resistance is defined by an elastic fracture (shear) stiffness ks and a stick-slip Coulomb threshold.

Use of 3DEC to Study Spalling and Deformation associated with Tunnelling at Depth

Blast Movement Simulation Through a Hybrid Approach of Continuum, Discontinuum, and Machine Learning Modeling

This work presents a hybrid modeling approach to efficiently estimate and optimize rock movement during blasting. A small-scale continuum model simulates early-stage, near-field blasting physics and generates synthetic data to train a machine learning (ML) model. Key parameters such as expanded hole diameter, burden velocity, and gas pressure are obtained through the ML model, which then inform a discontinuum model to predict far-field muckpile formation. The approach captures essential blast physics while significantly accelerating blast design optimization.