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The role of particle shape in computational modelling of granular matter

  • Technical Review
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Abstract

Granular matter is ubiquitous in nature and is present in diverse forms in important engineering, industrial and natural processes. Particle-based computational modelling has become indispensable to understand and predict the complex behaviour of granular matter in these processes. The success of modern computational models requires realistic and efficient consideration of particle shape. Realistic particle shapes in naturally occurring and engineered materials offer diverse challenges owing to their multiscale nature in both length and time. Furthermore, the complex interactions with other materials, such as interstitial fluids, are highly nonlinear and commonly involve multiphysics coupling. This Technical Review presents a comprehensive appraisal of state-of-the-art computational models for granular particles of either naturally occurring shapes or engineered geometries. It focuses on particle shape characterization, representation and implementation, as well as its important effects. In addition, the particles may be hard, highly deformable, crushable or phase transformable; they might change their behaviour in the presence of interstitial fluids and are sensitive to density, confining stress and flow state. We describe generic methodologies that capture the universal features of granular matter and some unique approaches developed for special but important applications.

Key points

  • Particle-based computational modelling that considers realistic particle shapes has become indispensable for understanding and predicting the complex behaviour of granular matter in engineering, industry and nature.

  • How to effectively represent the shape of a particle is closely related to its intended purpose; the modelling of naturally occurring granular materials may differ from approaches for engineered particles.

  • Particle shape representation is inseparably coupled to the detection of interparticle contacts, both of which critically determine the computational accuracy and efficiency of simulations of granular matter.

  • Specific methodologies are needed to address challenges arising from crushable particles or highly deformable particles, in which the co-evolution of particle shapes and sizes and hence contact detection algorithms dictate both accuracy and efficiency.

  • Consideration of shape effects in coupled simulations of granular particles and environmental fluids requires revamped theories and methods to faithfully reflect their underpinning multiphase, multiphysics nature.

  • Incorporating realistic particle shapes in granular matter modelling must harness the latest advances in parallel computing and machine learning for effective large-scale computations.

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Fig. 1: Modelling realistic complex particles and their collective behaviours.
Fig. 2: Numerical models on particle shape representation.
Fig. 3: Computational approaches for large-scale and multiscale modelling.

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Acknowledgements

J.Z. and S.Z. acknowledge the financial supports from the National Natural Science Foundation of China (via Project Nos 11972030 and 51909095) and Research Grants Council of Hong Kong (GRF Projects Nos 16206322, 16208720 and 16211221 and F-HKUST601/19). J.Z. also acknowledges the supports by the Project of Hetao Shenzhen-Hong Kong Science and Technology Innovation Cooperation Zone (HZQB-KCZYB-2020083) and the internal research supports provided by HKUST (FP907, IEG22EG01 and IEG22EG01PG).

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    Jidong Zhao & Shiwei Zhao

  2. The University of Twente, Enschede, The Netherlands

    Stefan Luding

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Zhao, J., Zhao, S. & Luding, S. The role of particle shape in computational modelling of granular matter. Nat Rev Phys 5, 505–525 (2023). https://doi.org/10.1038/s42254-023-00617-9

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