Introduction to Python scripting by reviewing key concepts and through demonstrations. Part 1 focuses on installing Python, variables and types, conditions and loops, and functions.
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.
This tutorial will show how to create and manipulate plot range elements in FLAC3D. Each plot-item in a plot may have one or more range elements that shows the portion which lies within the defined range, while removing from view the portion of the plot-item that lies outside it. Plot-item ranges may also be copied and applied to other plot-items.
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.
In this study, we address the issue of using graphs to predict flow as a fast and relevant substitute to classical DFNs. We consider two types of graphs, whether the nodes represent the fractures or the intersections between fractures.
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.