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.
This tutorial will show how to paint zone data onto an imported geometric surface in FLAC3D.
This video demonstrates using a library set of Building Blocks as a starting point for creating a new model. In this example, cylindrical blocks are snapped together to represent a tunnel and intersected with other blocks representing a nearby wall.
Mesh quality is crucial for the stability, accuracy, and fast convergence of numerical simulations. However, given the geometrical complexity of some models and the tools available for mesh creation, it is often necessary to accept meshes that deviate significantly from the known ideal shape.
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.