Python scripting is built into current versions of FLAC3D, 3DEC, and PFC. This video introduces users of Itasca software to working with Python and FLAC3D, 3DEC, and PFC types (zones, blocks, ball, structural elements, and so on). The Itasca Module, a comparison with FISH scripting, and object-oriented and array-oriented interfaces are reviewed and demonstrated.
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.
This tutorial illustrates how to generate movies from FLAC3D plots. It is also applicable for 3DEC, PFC, and UDEC.
The realism of Discrete Fracture Network (DFN) models relies on the spatial organization of fractures, which is not issued by purely stochastic DFN models. In this study, we introduce correlations between fractures by enhancing the genetic model (UFM) of Davy et al. [1] based on simplified concepts of nucleation, growth and arrest with hierarchical rules.
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.
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.