Learning

Customized Training

Customized Engineering Training Courses

Itasca Educational Partnership

ITASCA Academics

Software Tutorials

FLAC3D 7 0 Octree Mesh Tutorial

In this example, a pile of earth is modeled overlying undulating ground. This tutorial demonstrates how a FLAC3D model mesh can be easily created using DXF geometries and the ZONE DENSIFY command. How to differentiate parts of the model into separate GROUPs using DXF geometries and the GEOMETRY-SPACE range logic is also demonstrated.

Converting Plots to Data Files

Any model plot that you create interactively by adding plot-items and adjusting settings can be represented by an equivalent set of commands. This is useful should you want to include command-driven plotting in your modeling run.

FLAC3D 6 0 Model Generation using the Building Blocks Handle

Technical Papers

FLAC3D Soil-structure Model of a Building

A FLAC3D model of a raft foundation, multi-story building was used to assess the possibility of eliminating piles or jet-grouting columns from its initial design in favor of a thicker foundation. This would provide considerable savings in terms of costs, time, and site management.

Elastic Properties of Fractured Rock Masses With Frictional Properties and Power Law Fracture Size Distributions

We derive the relationships that link the general elastic properties of rock masses to the geometrical properties of fracture networks, with a special emphasis to the case of frictional crack surfaces.

We extend the well-known elastic solutions for free-slipping cracks to fractures whose plane resistance is defined by an elastic fracture (shear) stiffness ks and a stick-slip Coulomb threshold.

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.