This video is a recording of a one hour webinar reviewing the latest features in Version 6 of FLAC3D (currently available as a pre-release). Presented by Dr. David Russell, FLAC3D Product Manager and Lead Developer.
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.
Identifying fractures in the subsurface is crucial for many geomechanical and hydrogeological applications. Here, we assess the ability of the Ground Penetrating Radar (GPR) method to image open fractures with sub-mm apertures in the context of future deep disposal of radioactive waste.
This work presents a hybrid modeling approach to efficiently estimate and optimize rock movement during blasting. A small-scale continuum model simulates early-stage, near-field blasting physics and generates synthetic data to train a machine learning (ML) model. Key parameters such as expanded hole diameter, burden velocity, and gas pressure are obtained through the ML model, which then inform a discontinuum model to predict far-field muckpile formation. The approach captures essential blast physics while significantly accelerating blast design optimization.
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.