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Software Tutorials

FLAC3D 6.0 Interactive Model Pane

Using Python in Itasca Software

Python scripting is built into current versions of FLAC3D, 3DEC, and PFC. This video introduces users of Itasca software to working with Python and FLAC3D, 3DEC, and PFC types (zones, blocks, ball, structural elements, and so on). The Itasca Module, a comparison with FISH scripting, and object-oriented and array-oriented interfaces are reviewed and demonstrated.

Bonded Block Model undergoing Damage and Bulking during Simulated Relaxation

Continuum numerical modeling is inherently limited when the rock behavior involves mechanisms such as spalling and bulking. The Bonded Block Model (BBM) approach simulates the initiation of cracks that can coalesce and/or propagate leading to extension and shear fracturing, as well as the rock (e.g., intact, jointed, or veined) strength dependency on confinement.

Technical Papers

GPR-inferred fracture aperture widening in response to a high-pressure tracer injection test at the Äspö Hard Rock Laboratory, Sweden

We assess the performance of the Ground Penetrating Radar (GPR) method in fractured rock formations of very low transmissivity (e.g. T ≈ 10−9–10−10 m2/s for sub-mm apertures) and, more specifically, to image fracture widening induced by high-pressure injections. A field-scale experiment was conducted at the Äspö Hard Rock Laboratory (Sweden) in a tunnel situated at 410 m depth. The tracer test was performed within the most transmissive sections of two boreholes separated by 4.2 m. The electrically resistive tracer solution composed of deionized water and Uranine was expected to lead to decreasing GPR reflections with respect to the saline in situ formation water.

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.

Input to Orepass Design — A Numerical Modeling Study

Orepass design guidelines required for potentially continued mining at depth. Rock strength and stress state were validated through comparison with observed fallouts in orepasses and shafts and the optimal orientation and location of orepasses for future mining were determined.