Validation of DEM prediction for granular avalanches on irregular terrain

Stuart R. Mead*, Paul W. Cleary

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

19 Citations (Scopus)

Abstract

Accurate numerical simulation can provide crucial information useful for a greater understanding of destructive granular mass movements such as rock avalanches, landslides, and pyroclastic flows. It enables more informed and relatively low cost investigation of significant risk factors, mitigation strategy effectiveness, and sensitivity to initial conditions, material, or soil properties. In this paper, a granular avalanche experiment from the literature is reanalyzed and used as a basis to assess the accuracy of discrete element method (DEM) predictions of avalanche flow. Discrete granular approaches such as DEM simulate the motion and collisions of individual particles and are useful for identifying and investigating the controlling processes within an avalanche. Using a superquadric shape representation, DEM simulations were found to accurately reproduce transient and static features of the avalanche. The effect of material properties on the shape of the avalanche deposit was investigated. The simulated avalanche deposits were found to be sensitive to particle shape and friction, with the particle shape causing the sensitivity to friction to vary. The importance of particle shape, coupled with effect on the sensitivity to friction, highlights the importance of quantifying and including particle shape effects in numerical modeling of granular avalanches. Key Points Avalanche features are matched well between DEM simulations and an experiment The sensitivity of DEM to particle shape and friction is quantified Particle shape moderates and controls the effect of friction on avalanches

Original languageEnglish
Pages (from-to)1724-1742
Number of pages19
JournalJournal of Geophysical Research: Earth Surface
Volume120
Issue number9
DOIs
Publication statusPublished - 1 Sep 2015

Keywords

  • avalanche
  • depth-averaged models
  • discrete element method
  • landslide
  • numerical model
  • superquadric particle

Fingerprint

Dive into the research topics of 'Validation of DEM prediction for granular avalanches on irregular terrain'. Together they form a unique fingerprint.

Cite this