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OpenFOAM-avalanche 2312: depth-integrated models beyond dense-flow avalanches.

Authors :
Rauter, Matthias
Kowalski, Julia
Source :
Geoscientific Model Development. 2024, Vol. 17 Issue 17, p6545-6569. 25p.
Publication Year :
2024

Abstract

Numerical simulations have become an important tool for the estimation and mitigation of gravitational mass flows, such as avalanches, landslides, pyroclastic flows, and turbidity currents. Depth integration stands as a pivotal concept in rendering numerical models applicable to real-world scenarios, as it provides the required efficiency and a streamlined workflow for geographic information systems. In recent years, a large number of flow models were developed following the idea of depth integration, thereby enlarging the applicability and reliability of this family of process models substantially. It has been previously shown that the finite area method of OpenFOAM® can be utilized to express and solve the basic depth-integrated models representing incompressible dense flows. In this article, previous work is extended beyond the dense-flow regime to account for suspended particle flows, such as turbidity currents and powder snow avalanches. A novel coupling mechanism is introduced to enhance the simulation capabilities for mixed-snow avalanches. Further, we will give an updated description of the revised computational framework, its integration into OpenFOAM, and interfaces to geographic information systems. This work aims to provide practitioners and scientists with an open-source tool that facilitates transparency and reproducibility and that can be easily applied to real-world scenarios. The tool can be used as a baseline for further developments and in particular allows for modular integration of customized process models. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1991959X
Volume :
17
Issue :
17
Database :
Academic Search Index
Journal :
Geoscientific Model Development
Publication Type :
Academic Journal
Accession number :
179671479
Full Text :
https://doi.org/10.5194/gmd-17-6545-2024