Discrete Element Method (DEM) for Industrial Applications: Comments on Calibration and Validation for the Modelling of Cylindrical Pellets

By Michele Marigo, E. Hugh Stitt. 2015

253 citations recorded by the source corpus.

As a consequence of increasing computer power and more readily useable commercial and open source codes, Discrete Element Method (DEM) is becoming widely used across a range of applications to simulate increasingly complex processes. This is exacerbating the challenge of setting up simulations for industrial applications. The literature on input parameter selection is divided. A number of papers report methods for their direct measurement. Others, by contrast, propose a “calibration” approach where the particle properties are derived as adjustable parameters by quantitative comparison of experimental and simulation results. This paper reports on the calibration and validation of the input parameters for the specific case of cylindrical tablets represented by conjoined spheres. The initial steps are to not only assign and optimise the DEM input parameters but also optimise the shape representation; what degree of linearity of the edges and angularity of the corners are required to accurately reflect the cylindrical shape. The model was used to simulate two configurations of a rotating drum: an “attrition tester” with a single longitudinal baffle and an un-baffled drum. The results were compared qualitatively and quantitatively with experimental data. While the qualitative comparison was good in most cases, detailed quantitative comparison fared less well, with some significant errors. This study highlights some of the key issues for a wider-spread of industrial applications for DEM.

Subfields: Civil and Structural Engineering, Computational Mechanics, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/20dc1f2a433d2210574f523a0029db557f68a9d1

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Civil and Structural Engineering

1. Z. Yan
2. Sam K. Wilkinson
3. Michele Marigo
4. E. Hugh Stitt
5. C. Coetzee

In Computational Mechanics

1. Z. Yan
2. Sam K. Wilkinson
3. Michele Marigo
4. E. Hugh Stitt
5. C. Coetzee

In Mechanical Engineering

1. Z. Yan
2. Sam K. Wilkinson
3. Michele Marigo
4. E. Hugh Stitt
5. C. Coetzee

Citations in the corpus

• Discrete element modelling (DEM) input parameters: understanding their impact on model predictions using statistical analysis (2015, methodology): “A common approach is to choose the DEM input parameters by calibrating the DEM model against bulk global measurements and then to adjust these input parameters until the outputs match the experimental, usually macroscopic, observations [27].”