Learning

Customized Training

Training

Customized Engineering Training Courses

Itasca Educational Partnership

ITASCA Academics

Software Tutorials

FLAC3D 7.0 Unstructured Mesh Tutorial

A tutorial showing how to create an unstructured mesh in FLAC3D 7.0 using the extruder pane.

FLAC3D 6.0 PFC Plugin Conveyor

FLAC3D 6.0 Built-in Model Generation Tools and Workflow

Building Blocks works seamlessly with the FLAC3D 6.0 extruder tool and new Model Pane. Building Blocks includes a library of model primates and users can also add and load their own building block sets.

Technical Papers

Flowback Test Analyses at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) Site

Injection testing conducted in 2017 and 2019 at the Frontier Observatory for Research in Geothermal Energy site in Utah evaluated flowback as an alternative to prolonged shut-in periods to infer closure stress, formation compressibility, and formation permeability. Flowback analyses yielded lower inferred closure stresses than traditional shut-in methods and indicated high formation compressibility, suggesting an extensive fractured system. Numerical simulations showed rebound pressure is not necessarily the lower bound of minimum principal stress. Stiffness changes can be identified as depletion transitions from hydraulic to natural fractures. The advantage if flowback is reduced time to closure.

A Strategic Rock Mechanics Study for The Kevitsa Open Pit Mine

The Boliden Kevitsa open pit mine is revising its strategic plan with a new pit optimization project undertaken to investigate an increase in production.

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.