An Introduction to Python Scripting: Part 2

Introduction to Python scripting by reviewing key concepts and through demonstrations. Part 2 focuses on classes and objects plus lists and dictionaries.

FLAC3D 6 0 Model Generation using the Building Blocks Handle

MINEDW Tutorial (Part 4: Meshing)

In this tutorial we will go over meshing, from the creation of a 2D mesh and how to import it to MINEDW, to the inclusion of topography, layers, and pinch-outs to different areas of interest in the model.

Influence of the particle shape on the impact force of lahar on an obstacle

Lahars represent natural phenomena that can generate severe damage in densely populated urban areas. The evaluation of pressures generated by these mass flows on constructions (buildings, infrastructure…) is crucial for civil protection and assessment of physical vulnerability. The existing tools to model the spread of flows at large scale in densely populated urban areas remain inaccurate in the estimation of mechanical efforts. A discrete numerical model is developed for evaluating debris flow (DF) impact pressures at the local scale of one structure.

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.

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.