Vancouver, BC, Canada
Denver, Colorado, USA
Lima, Peru (presented in Spanish)
Brisbane, Queensland, Australia
Notes: Please contact us for prices or to enquire about discounts when sending multiple people from your company along. Minimum and maximum course numbers apply. Muk3D licenses will be provided to all attendees for the duration of the course. Includes course notes, coffee, and lunch.
Introduction to Muk3D Formation for simple 3D modeling. This session will focus on the basic 3D tools available in Muk3D Formation that are aimed at basic geotechnical, mining, and surface water management tasks.
A brief introduction to Muk3D Tailings+ will be provided, covering:
The source data will be one of our training datasets for the first part of the day. If there is a suitable client dataset this can be used for the second part of the day.
This session covers modelling of TSF's with Tailings+. The primary focus is on long range planning. The examples presented on this day will be based on client supplied data and be focused on active projects.
The preference is to work with active client projects for this training.
Participants new to Muk3D Tailings+ will have a broad understanding of the capabilities of the model and have strategies for approaching different tailings deposition problems.
Participants who have experience will Muk3D will have the opportunity to improve their understanding of some of the advanced features of the software.
This session is an introduction to macros and scripting with Python in Muk3D. Python is a high-level language that allows users to customise and automate aspects of Muk3D to simplify repetitive design tasks and automate workflows.
Participants are expected to have at least a basic understanding of the fundamentals of programming (e.g. loops, control structures) and some basic experience in scripting in Excel/VBA or other scripting or programming languages.
By the end of the session participants are expected to be able to record some simple macros in Muk3D, customise them by requesting data from the user, use loops to run different models using different input values, and undertake some basic batch processing of output data using Macros.