This tutorial will guide you through how to create a fractured Synthetic Rock Mass (SRM) specimen.
In this tutorial, we review how to automatically skin models, identify and group zone faces, and interactively select and group zones and zone faces. This tutorial also illustrates using the Model Pane to interactively add a shell structural element along a tunnel.
In this tutorial we will explore all the visualization components that MINEDW has to offer, and all the options available to the user to visualize the model's components and properties.
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.
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.