Analytical and Numerical Solutions for Three-Dimensional Granular Collapses

This research paper presents a comprehensive approach to investigating dry granular collapses in three dimensions, by combining analytical, numerical, and experimental methods. The experimental investigation utilised a novel apparatus to study granular collapses in the laboratory. It is demonstrated that a quasistatic understanding of granular collapses can accurately predict the final normalised run-out distances for dynamic granular collapses. Our approach involved establishing a correlation between the angle of repose and the initial aspect ratio of the granular column. It is also shown that the material point method (MPM) is suitable for modelling granular collapses in three dimensions. Our in-house solver was further validated using experimental evidence under an explicit formulation, resulting in good agreement between the numerical and experimental results. The findings demonstrate the effectiveness of our in-house solver for three-dimensional granular collapse modelling.

Automated summary

This research paper presents a comprehensive approach to investigating dry granular collapses in three dimensions, by combining analytical, numerical, and experimental methods. The experimental investigation utilised a novel apparatus to study granular collapses in the laboratory. It is demonstrated that a quasistatic understanding of granular collapses can accurately predict the final normalised run-out distances for dynamic granular collapses. Our approach involved establishing a correlation between the angle of repose and the initial aspect ratio of the granular column. It is also shown that the material point method (MPM) is suitable for modelling granular collapses in three dimensions. Our in-house solver was further validated using experimental evidence under an explicit formulation, resulting in good agreement between the numerical and experimental results. The findings demonstrate the effectiveness of our in-house solver for three-dimensional granular collapse modelling.