Working with Email in Itasca Software

Learn how you can use commands and functions to send email messages and attachments via Itasca software. Use this capability to inform you when a model has finished running, a result is available (even attach a plot), or the model run is interrupted.

FLAC3D 7.0 Structured Mesh Tutorial

A tutorial showing how to create a structured mesh in FLAC3D 7.0 using the extruder pane.

Tutorial: Simple Slope Stability

Using UDEC 6 and the shear-reduction method to calculate the factor-of-safety, this tutorial will show you how to analyze the stability of a simple slope containing: (1) no discrete jointing (continuum), (2) fully-continuous jointing (discrete blocks), and (3) noncontinuous, en echelon jointing.

On the Density Variability of Poissonian Discrete Fracture Networks, with application to power-law fracture size distributions

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.

A Discrete Fracture Network Model With Stress-Driven Nucleation: Impact on Clustering, Connectivity, and Topology

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.

Blast Movement Simulation Through a Hybrid Approach of Continuum, Discontinuum, and Machine Learning Modeling

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.

  • ITASCA Strengthens North American Delivery of Integrated Geomechanics and Hydrogeology Solutions Drawing on decades of geomechanical and hydrogeological expertise, ITASCA has announced the formation of ITASCA...
  • Itasca has announced the release of FLAC2D v9 Itasca has announced the release of FLAC2D v9, revolutionizing the way we analyze and predict...
  • 6th Itasca Symposium on Applied Numerical Modeling The next Itasca Symposium will take place June 3 - 6, 2024, in Toronto, Canada....