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Cited by 462

The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.

A two-fluid model for avalanche and debris flows

Pitman, E. Bruce, Le, Long·2005·Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences

Abstract

Geophysical mass flows—debris flows, avalanches, landslides—can contain O (10 6 –10 10 ) m 3 or more of material, often a mixture of soil and rocks with a significant quantity of interstitial fluid. These flows can be tens of meters in depth and hundreds of meters in length. The range of scales and the rheology of this mixture presents significant modelling and computational challenges. This paper describes a depth-averaged ‘thin layer’ model of geophysical mass flows containing a mixture of solid material and fluid. The model is derived from a ‘two-phase’ or ‘two-fluid’ system of equations commonly used in engineering research. Phenomenological modelling and depth averaging combine to yield a tractable set of equations, a hyperbolic system that describes the motion of the two constituent phases. If the fluid inertia is small, a reduced model system that is easier to solve may be derived.

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Crossref · 10.1098/rsta.2005.1596

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Metadata

Authors
Pitman, E. B., & Le, L.
Venue
Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences
Published
2005-07
Volume
363
Issue
1832
Pages
1573-1601
ISSN
  • 1364-503X (ISSN-L)
  • 1471-2962
OpenAlex
W2139170886
Cited by
462
References
11
FWCI
28.03
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: A two-fluid model for avalanche and debris flows. https://app.cochat.ai/papers/10.1098/rsta.2005.1596
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Pitman, E. B., & Le, L. (2005). A two-fluid model for avalanche and debris flows. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. https://doi.org/10.1098/rsta.2005.1596

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.