Learning

Customized Training

Customized Engineering Training Courses

Itasca Educational Partnership

ITASCA Academics

Software Tutorials

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.

Fluid Flow through Jointed Rock

As well as flow through joints, 3DEC 5.2 is capable of simulating fluid flow through the blocks or the matrix (i.e., between the joints). It is assumed that the blocks represent a saturated, permeable solid, such as soil or fractured rock mass.

FLAC3D 6.0 Model Generation using the Building Blocks and Geometric Data Sets

Technical Papers

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.

Use of a Chemical Transport Code for the Prediction of Gold Heap Leach Production

Itasca Denver, Inc., (Itasca) in conjunction with Newmont Mining Corporation (NMC) developed a numerical model to estimate gold (Au) production from NMC’s heap-leach operations.

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.