Morphology characterization and discrete element modeling of coral sand with intraparticle voids

Huang, Shuai; Huang, Linchong; Lai, Zhengshou; Zhao, Jidong

doi:10.1016/j.enggeo.2023.107023

Cited by 18 publications

(1 citation statement)

References 54 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The node-to-surface detection algorithm promises to address the issues in vertex-vertex or triangle-triangle contact detection and has been used for SH-based methods 57,95,96 . More recently, the level-set and signed-distance field (SDF) functions originally used in computer graphics are attracting increasing attention for application in advanced DEM to accelerate node-to-surface detection, such as level-set-based DEM [97][98][99] and SDF-based DEM [100][101][102] .…”

Section: Technical Reviewmentioning

confidence: 99%

The role of particle shape in computational modelling of granular matter

Zhao,

Luding

2023

Nat Rev Phys

Self Cite

View full text Add to dashboard Cite

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. Sections• 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.Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

show abstract