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.
A tutorial showing how to create an unstructured mesh in FLAC3D 7.0 using the extruder pane.
This tutorial will guide you through how to create a simple material using the linear parallel bond-model.
Hydraulic testing using wireline deployed water-inflated packers is becoming a common practice for groundwater characterization at mining sites.
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.
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.