Learning

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Software Tutorials

Tutorial: Simple Slope Stability

Using UDEC 6 and the shear-reduction method to calculate the factor-of-safety, this tutorial will show you how to analyze the stability of a simple slope containing: (1) no discrete jointing (continuum), (2) fully-continuous jointing (discrete blocks), and (3) noncontinuous, en echelon jointing.

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.

FLAC3D 6.0 PFC Plugin Conveyor

Technical Papers

Graph-based flow modeling approach adapted to multiscale discrete-fracture-network models

In this study, we address the issue of using graphs to predict flow as a fast and relevant substitute to classical DFNs. We consider two types of graphs, whether the nodes represent the fractures or the intersections between fractures.

The nexus between groundwater modeling, pit lake chemogenesis and ecological risk from arsenic in the Getchell Main Pit, Nevada, U.S.A.

The proliferation of mine pits that intersect the groundwater table has engendered interest in environmental consequences of the lakes that form after cessation of dewatering.

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.