Discrete Element Method (DEM): Theory and hands-on practice
The majority of all products sold worldwide either are particles, or involve particles at some stage of production. In contrast to fluids, theoretical understanding of particulate systems is at an early stage and difficult to predict, largely due to the distribution of many properties (size, shape, cohesivity etc.) throughout the powder population. The Discrete Element Method (DEM) is the primary modelling approach to enable prediction of how particles behave in a certain processing situation. DEM enables investigation into the influence of material properties and processing conditions on the process outcome and can provide valuable insights to enable manufacturers to make informed decisions about process and formulation optimisation.
In this course you will be introduced to the underlying theory and practical considerations of DEM on Day 1, including fundamental governing principles; models to account for elasticity, plasticity and cohesion; how to calibrate particle properties; and utilisation of AI and machine learning. On Day 2 you will get hands-on training and guided practice on the most widely used DEM software, EDEM (Altair Engineering), through a series of case studies. Day 3, depending upon interest, will comprise of a seminar/mini conference where researchers and practitioners demonstrate how they’ve utilised DEM to gain process understanding.
No prior knowledge of DEM/particle simulation methods is required.
No previous programming experience is required.
If you are familiar with the theory of DEM but unfamiliar with EDEM software, then you could opt to only attend Day 2. If you just want to learn the theory, then you could attend just Day 1. If you attend both Day 1 & 2, then Day 3 is included free-of-charge.
If you’re interested in this course, please state if you are a student and which day(s) you’re interested to attend.
For more information on this course, please contact llahub@newcastle.ac.uk or enquire here
Learning Outcomes
Understanding of the fundamentals of DEM and how to calibrate material properties (Day 1); Capability to setup, run and analyse DEM simulations using EDEM software (Day 2).
Course Agenda
Day 1: Introduction to granular materials and DEM fundamentals, contact models, material calibration, utilising AI/machine learning.
Day 2: Introduction to the EDEM environment, hands-on practice through a series of case studies.
Day 3: (Dependent upon enough interest) Presentations from researchers and industrial practitioners on applications of DEM.
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