Erosion and Transport of Dry Soil Bed by Collisional Granular Flow: Insights From a Combined Experimental–Numerical Investigation

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Jiang, Y.; Song, P.; Choi, C.E.; Choo, J.: Erosion and Transport of Dry Soil Bed by Collisional Granular Flow: Insights From a Combined Experimental–Numerical Investigation. In: Journal of Geophysical Research: Earth Surface 128 (2023), Nr. 9, e2023JF007073. DOI: https://doi.org/10.1029/2023jf007073

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To cite the version in the repository, please use this identifier: https://doi.org/10.15488/16248

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Abstract: 
Collision-induced stresses on soil beds under granular geophysical flows have been demonstrated to be highly erosive. However, it remains mostly elusive as to how a collisional granular flow erodes and transports soil bed material. This paper presents a combined experimental and numerical investigation into the mechanisms underlying collision-induced erosion and transport of dry soil beds. A series of flume experiments are conducted where collisional granular flows erode dry sand beds under varied conditions. The experiments are then back-analyzed using a hybrid continuum–discrete simulator to gain physical insight into the erosion and transport processes. Results show that the key mechanism of collision-induced erosion and transport is the retexturing of the soil bed surface. This implies that bed morphology, which has often been overlooked in mobility and hazard assessments, has profound effects on erosion and transport potential. Further, contrary to most existing models that assume all the eroded bed volume is carried away by granular flow, it is found that only up to 80% of the eroded material is transported. Also found is that the collisional stresses of the monodisperse grains in this study follow the Pareto distribution in which 80% of differences in the outcomes are due to 20% of causes. This finding suggests that there is measurable certainness in a seemingly random process of coarse grain collisions with an erodible soil bed.
License of this version: CC BY-NC 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2023
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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1 image of flag of Germany Germany 6 42.86%
2 image of flag of United States United States 4 28.57%
3 image of flag of India India 1 7.14%
4 image of flag of Ireland Ireland 1 7.14%
5 image of flag of France France 1 7.14%
6 image of flag of China China 1 7.14%

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