Learning

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Software Tutorials

Proppant in Fluid Filled Joints

The transport and placement of proppant within fractures is modeled in 3DEC by representing the proppant and fracturing fluid as a mixture.

FLAC3D 6.0 Model Generation using the Building Blocks and Geometric Data Sets

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

Three-dimensional Modeling and Stress Calibration for a Complex Mining Geometry

Study stress situation for potential continued mining towards greater depths; stress calibration against stress measurements using numerical modeling; and use of calibrated model to study stresses at existing infrastructure, study stresses at potential future haulage level locations, and as input to local models.

Simulation of Three-Dimensional Pore-Pressure Distribution for Slope-Stability Analysis

A 3D groundwater flow model was constructed using MINEDW [1] to simulate pore pressure at the Chuquicamata open pit mine slope in Chile.

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.