Learning

Software Tutorials

PFC 7 Balls in a Box

This tutorial will guide you through the main steps required to build a simple PFC model with 30 interacting balls in a box using the linear contact model.

Plotting Borehole Core Data using Geometry and FISH

In this example, you will see how to create your own custom plot of drill core data containing location, orientation, depth, and geotechnical data (lithography. fracture count, rock strength, weathering, and RMR).

MINEDW Tutorial (Part 1: Menu Options)

In this tutorial we will briefly cover the MINEDW user interface, its components, and the MINEDW Menu with the different options and tools it provides to build numerical models.

Technical Papers

Connectivity, permeability, and channeling in randomly distributed and kinematically defined discrete fracture network models

A major use of DFN models for industrial applications is to evaluate permeability and flow structure in hardrock aquifers from geological observations of fracture networks. The relationship between the statistical fracture density distributions and permeability has been extensively studied, but there has been little interest in the spatial structure of DFN models, which is generally assumed to be spatially random (i.e., Poisson). In this paper, we compare the predictions of Poisson DFNs to new DFN models where fractures result from a growth process defined by simplified kinematic rules for nucleation, growth, and fracture arrest.

A Calibrated Predictive Geochemical Model of Leaching and Attenuation Reactions in a Mine Pit Lake

A geochemical model was developed to predict future water quality of the Cove pit lake in support of site closure and regulatory permitting.

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.

Latest News
  • 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...
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  • WEBINAR: Solving Geothermal Challenges with XSite Numerical Modeling ITASCA Software and Baker Hughes are hosting a collaborative webinar to demonstrate how combining advanced...
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  • Itasca has announced the release of FLAC2D v9 Itasca has announced the release of FLAC2D v9, revolutionizing the way we analyze and predict...
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Upcoming Events
15 Sep
ITASCA at EUROCK 2026: Advancing Innovation in Rock Engineering
ITASCA is pleased to announce its participation in EUROCK 2026 – ISRM Regional Symposium, taking place from 15–19 September 2026 in Sko... Read More
20 Sep
ITASCA to Participate in CouFrac 2026
ITASCA will be participating in CouFrac 2026, taking place from 20–23 September 2026 in Uppsala, Sweden. The conference brings together... Read More
26 Oct
ITASCA at Slope Stability 2026: Strategic Sponsor and Technical Contributor_2
ITASCA is proud to participate as a Strategic Sponsor in Slope Stability 2026, one of the world’s leading international symposiums focu... Read More