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Software Tutorials

PFC 7 Balls in a Box

This tutorial will guide you through the main steps required to build a simple PFC model with 30 interacting balls in a box using the linear contact model.

Working with ParaView

Itasca has made it easy to readily export model data from FLAC3D and 3DEC software (version 7+) using the VTK file format.

Loops, Splitting, and Operators

When constructing or running simulations, you may want to query or modify values associated with all, or some of, the objects in your model (such as zones, nodes, blocks, balls, contacts, rockbolts, etc.). This may be to measure results like stress or displacement, to assign a calculated extra variable for plotting, or to adjust a property value. There are several ways to identify and navigate across all these objects using loops, splitting, and operators — with each one becoming easier and faster to execute. See how you can apply all of these approaches in a tutorial where a zone property is randomly assigned for strength variability throughout the model. You will also see how much easier and faster these approaches have become. Applying model property distributions via the PROPERTY command is also reviewed.

Technical Papers

Advanced three-dimensional geomechanical and hydrogeological modelling for a deep open pit

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.

Connectivity, permeability, and channeling in randomly distributed and kinematically defined discrete fracture network models

A major use of DFN models for industrial applications is to evaluate permeability and flow structure in hardrock aquifers from geological observations of fracture networks. The relationship between the statistical fracture density distributions and permeability has been extensively studied, but there has been little interest in the spatial structure of DFN models, which is generally assumed to be spatially random (i.e., Poisson). In this paper, we compare the predictions of Poisson DFNs to new DFN models where fractures result from a growth process defined by simplified kinematic rules for nucleation, growth, and fracture arrest.