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Training

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Tutoriels Logiciels

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).

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.

Working with Building Blocks in FLAC3D 6 (Part 1)

This video demonstrates using a library set of Building Blocks as a starting point for creating a new model. In this example, cylindrical blocks are snapped together to represent a tunnel and intersected with other blocks representing a nearby wall.

Articles scientifiques

Tunneldrivning i heterogena förhållanden

InledningProblem: Brist på erfarenhet av tunneldrivning i heterogena förhållanden med konventionell uttagsteknik (borrning och sprängning).

Mål: Fördjupa kunskapen och förståelse av brott och deformationsmönster vid dessa förhållanden.

The role of rock mass heterogeneity and buckling mechanisms in excavation performance in foliated ground at Westwood Mine, Quebec

Operations at Westwood mine in Quebec, Canada were temporarily halted in May 2015 after three large-magnitude seismic events occurred over two days. The mechanisms leading to these events, which caused severe damage to several accesses, were not well understood at first. This paper presents the key aspects of FLAC3D back-analysis modelling, which include (1) an anisotropic rock mass strength model with properties derived from field and laboratory strength testing, and (2) a scheme to account implicitly for the deconfinement that accompanies buckling around excavations.

On the Density Variability of Poissonian Discrete Fracture Networks, with application to power-law fracture size distributions

This paper presents analytical solutions to estimate at any scale the fracture density variability associated to stochastic Discrete Fracture Networks. These analytical solutions are based upon the assumption that each fracture in the network is an independent event. Analytical solutions are developed for any kind of fracture density indicators.