In this tutorial we will explore all the visualization components that MINEDW has to offer, and all the options available to the user to visualize the model's components and properties.
Any model plot that you create interactively by adding plot-items and adjusting settings can be represented by an equivalent set of commands. This is useful should you want to include command-driven plotting in your modeling run.
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.