粟滨

个人信息Personal Information

教师拼音名称:subin

出生日期:1995-03-27

电子邮箱:

入职时间:2023-07-03

所在单位:土木工程学院

职务:助理实验师

学历:研究生(硕士)毕业

办公地点:中南大学铁道学院第二综合实验楼

性别:男

联系方式:subin95@csu.edu.cn

学位:硕士学位

在职信息:在职

毕业院校:中南大学

学科:土木工程

论文成果

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Exploring debris-flow dynamics under basal friction: Insights from an enhanced 3D-SPH coulomb–viscoplastic sliding boundary

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DOI码:10.1016/j.compgeo.2025.107317

发表刊物:Computers and Geotechnics

关键字:Debris flow; Basal friction; SPH; Coulomb-viscoplastic model; Boundary condition

摘要:Basal friction is fundamental to understanding debris-flow behavior as it strongly influences transport dynamics, energy dissipation, and sediment deposition on rough channel beds. Although frictional effects are well addressed in mesh-based continuum models, incorporating them into Lagrangian particle based frameworks remains challenging due to complex interfacial interactions and truncation errors. To bridge this gap, we integrate the Coulomb-Viscoplastic Sliding Boundary (CVSB) into a 3D-SPH scheme, enabling adaptive capture of sliding behavior and enhancing simulation accuracy over rough channels. Unlike conventional no-slip treatment, the CVSB explicitly incorporates basal friction via a friction coefficient and prescribes a pressure- and deformation dependent sliding velocity, in accordance with Coulomb friction laws and debris-flow rheology. The newly developed CVSB is embedded in a modified Dynamic Boundary Condition (mDBC) framework and integrated into our existing HBP-SPH model. Validation against a series of full-scale flume experiments with varying surface configurations demonstrates that the CVSB-based SPH model accurately reproduces experimental observations, including flow-front evolution, propagation velocity profile, and runout areas. Sensitivity analyses further reveal that higher basal friction amplifies debris-flow responsiveness to rheological fluctuations, underscoring its potential impact on the relative contributions of inertial and viscous effects in debris-flow motion. Overall, the proposed model demonstrates significant potential for improving disaster mitigation strategies by providing enhanced predictions of flow propagation and deposition.

备注:中科院一区、TOP期刊

合写作者:(中科院一区、TOP期刊) Su Bin, Han Zheng, Ma Yangfan (Corresponding author), Li Yange, Ding Haohui, Chen Guangqi

论文类型:期刊论文

论文编号:107317

卷号:185

页面范围:107317

是否译文:

发表时间:2025-04-30

收录刊物:SCI