Particle shape characterisation and its application to discrete element modelling--颗粒学报PARTICUOLOGY

Williams, K. C., Chen, W., Weeger, S., & Donohue, T. J. (2014). Particle shape characterisation and its application to discrete element modelling. Particuology, 12, 80–89. https://doi.org/10.1016/j.partic.2013.02.014

Particle shape characterisation and its application to discrete element modelling

Kenneth C. Williams ^a *, Wei Chen ^a, Sebastian Weeger ^b, Timothy J. Donohue ^c

a Centre for Bulk Solids and Particulate Technologies, Newcastle Institute for Energy and Resources, The University of Newcastle, Callaghan 2308, Australia
b Georg-Simon-Ohm University Nuremberg, Nuremberg 90121, Germany
c TUNRA Bulk Solids, Newcastle Institute for Energy and Resources, The University of Newcastle, Callaghan 2308, Australia

10.1016/j.partic.2013.02.014

Volume 12, February 2014, Pages 80-89

Received 29 December 2012, Revised 19 February 2013, Accepted 28 February 2013, Available online 31 July 2013.

E-mail: Ken.Williams@newcastle.edu.au; kcwillia2@bigpond.com

Highlights

• Two image segmentation programmes were developed to obtain particle shape descriptors.

• Separated and lumped particle images were analysed and reconstructed.

• Two-dimensional shape descriptor parameters were extracted from particles images.

• Irregularly shaped DEM particles were generated utilising the particle shape descriptors.

Abstract

Increasing importance has been placed on particle shape implementation within discrete element modelling (DEM) in order to more accurately reflect the non-spherical behaviour of the bulk material being handled. As computational resources grow, complex particle shapes are increasingly being modelled as the associated simulation times become more realistic to provide timely solutions. The objective of this research is to assess particle shape descriptors through a digital image segmentation technique, and to further implement particle shape parameters into generation of corresponding irregular shaped DEM particles. Separated and lumped particle images were analysed and reconstructed through the development of two distinct methodologies. Subsequently, various particle shape descriptors were obtained using combinations of image segmentation algorithms, including mathematical morphology processing, thresholding, edge detection, region growing, region splitting and region merging. DEM particles were subsequently created using particle shape results obtained above. Shape parameters of DEM particles were then examined and validated against the real particle shape parameters.

Graphical abstract

Keywords

Particle shapes; Particle morphology; Image segmentation; Discrete element modelling

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