Learning

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Software Tutorials

An Introduction to Python Scripting: Part 1

Introduction to Python scripting by reviewing key concepts and through demonstrations. Part 1 focuses on installing Python, variables and types, conditions and loops, and functions.

Command Conversion Tool

Learn how to automatically convert old FLAC3D and 3DEC data files and FISH functions into the most current software version.

Tunnel Pulse with Quiet Boundaries

A pressure pulse is being applied to the tunnel boundary with a frequency of 4 Hz over tens of milliseconds. Quiet (i.e., viscous) boundaries have been applied to all but the top of the model, which remains a free surface.

Technical Papers

The role of rock mass heterogeneity and buckling mechanisms in excavation performance in foliated ground at Westwood Mine, Quebec

Operations at Westwood mine in Quebec, Canada were temporarily halted in May 2015 after three large-magnitude seismic events occurred over two days. The mechanisms leading to these events, which caused severe damage to several accesses, were not well understood at first. This paper presents the key aspects of FLAC3D back-analysis modelling, which include (1) an anisotropic rock mass strength model with properties derived from field and laboratory strength testing, and (2) a scheme to account implicitly for the deconfinement that accompanies buckling around excavations.

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.

On the Density Variability of Poissonian Discrete Fracture Networks, with application to power-law fracture size distributions

This paper presents analytical solutions to estimate at any scale the fracture density variability associated to stochastic Discrete Fracture Networks. These analytical solutions are based upon the assumption that each fracture in the network is an independent event. Analytical solutions are developed for any kind of fracture density indicators.