Landslide dynamics with energy loss in internal shearing

剪切(物理) 机械 消散 山崩 内能 粒状材料 岩土工程 动力摩擦 地质学 经典力学 材料科学 物理 量子力学 热力学 复合材料
作者
Shiva P. Pudasaini,Martin Mergili
出处
期刊:Landslides [Springer Science+Business Media]
标识
DOI:10.1007/s10346-024-02424-4
摘要

Abstract As a crucial physical parameter, inter-particle friction plays a dominant role in the deformation, motion, and spreading of granular landslides. However, existing functional landslide models ignore the frictional energy loss in the internal shearing of granular material. Here, we propose a novel dynamical model that includes the frictional energy loss in internal shearing during the mass transport, making it a more complete landslide dynamical equation, for the first time, capable of describing the frictional energy dissipation. It includes a dimensionless intrinsic quantity describing the strength of frictional energy loss in internal shearing, internal friction angle, and dynamical quantities: the force induced by free-surface gradient, local extensional-compressional mode, slip velocity along the granular surface, and material weight. We access the model performance by presenting contrasting scenarios. Simulation results, including the 1903 Frank Slide, demonstrate the importance of frictional energy loss in actively controlling the deformation, motion, and deposition of sheared granular flows. Profiles and geometries are fundamentally different without and with considering frictional energy loss in granular shearing. Deposition structures appear more realistic for simulations with frictional energy loss, in line with observation, revealing the importance of frictional energy loss in internal shearing. This demonstrates, classical models, based solely on the basal Coulomb friction, cannot properly control the landslide dynamics. In contrast, the new model more accurately simulates the landslide propagation, run-out, spreading, and its fan morphology. This suggests the need to complement existing mass flow models with the new frictional energy loss principle in granular shearing in physically legitimately controlling the mass spreading, motion, and deposition.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
御觞丶发布了新的文献求助10
刚刚
喵拟吗喵完成签到,获得积分10
刚刚
1秒前
2秒前
2秒前
2秒前
3秒前
Owen应助要减肥的高山采纳,获得10
3秒前
赘婿应助cat采纳,获得10
4秒前
One应助Wxj246801采纳,获得20
5秒前
DrLinh完成签到,获得积分10
5秒前
6秒前
BookerM完成签到,获得积分10
6秒前
6秒前
琴power发布了新的文献求助10
8秒前
Polly完成签到,获得积分10
8秒前
cyy发布了新的文献求助10
8秒前
俊俏的紫菜完成签到,获得积分10
10秒前
10秒前
Jasper应助林渤森采纳,获得30
10秒前
11秒前
大模型应助英勇亦绿采纳,获得10
11秒前
沐颜发布了新的文献求助10
12秒前
Luojiayi发布了新的文献求助20
12秒前
12秒前
一方通行发布了新的文献求助10
12秒前
moonveil发布了新的文献求助10
12秒前
13秒前
饱满一手完成签到 ,获得积分10
13秒前
要减肥的高山完成签到,获得积分10
14秒前
14秒前
想见你发布了新的文献求助10
14秒前
自觉画笔完成签到 ,获得积分10
15秒前
活泼秋玲完成签到,获得积分10
16秒前
左氧氟沙星完成签到,获得积分10
16秒前
16秒前
鸢尾绘画发布了新的文献求助10
16秒前
18秒前
18秒前
19秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1500
Instituting Science: The Cultural Production of Scientific Disciplines 666
Signals, Systems, and Signal Processing 610
The Organization of knowledge in modern America, 1860-1920 / 600
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6360182
求助须知:如何正确求助?哪些是违规求助? 8174316
关于积分的说明 17216935
捐赠科研通 5415033
什么是DOI,文献DOI怎么找? 2865763
邀请新用户注册赠送积分活动 1843055
关于科研通互助平台的介绍 1691258