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Digital Twin Modeling for Landslide Risk Scenarios in Mountainous Regions

文献类型：期刊论文

作者Li, Lai1,4,5; Tang, Bohui1,2,4,5; Cai, Fangliang1,4,5; Wei, Lei1,3,4,5; Zhu, Xinming1,4,5; Fan, Dong1,4,5
刊名SENSORS
出版日期2026-01-08
卷号26期号:2页码:421
关键词rain-induced landslide digital twins displacement mutation sensitive zone landslide monitoring Multiphysics coupling
DOI10.3390/s26020421
产权排序4
文献子类Article
英文摘要Highlights A novel 3D digital twin framework for landslides is developed using a closest-packed spherical discrete element model. The point-contact mechanism of spherical elements simplifies friction modeling and enhances computational efficiency. Steady-state slope stress exhibits a trapezoidal distribution, increasing from the surface inwards. The stress increases uniformly from 0 kPa at the surface to 210 kPa in the innermost region. What are the main findings? A sensitive zone of the landslide mass was identified in the numerical simulations. Both stress and displacement results consistently showed the highest concentration at one-tenth of the slope height above the toe, rather than at the crest or base. Advanced Simulation Framework: The novel 3D digital twin approach improves computational efficiency and enables realistic landslide evolution mapping. What are the implications of the main findings? This finding offers a new perspective for future research, as the identified stress and displacement concentration zone provides a tangible focus for further investigation. Advanced Predictive Modeling: The 3D digital twin framework provides a more stable method for simulating landslides. This approach introduces a physics-driven framework, effectively addressing the lack of realistic physical parameters in conventional hazard scenario modeling.Highlights A novel 3D digital twin framework for landslides is developed using a closest-packed spherical discrete element model. The point-contact mechanism of spherical elements simplifies friction modeling and enhances computational efficiency. Steady-state slope stress exhibits a trapezoidal distribution, increasing from the surface inwards. The stress increases uniformly from 0 kPa at the surface to 210 kPa in the innermost region. What are the main findings? A sensitive zone of the landslide mass was identified in the numerical simulations. Both stress and displacement results consistently showed the highest concentration at one-tenth of the slope height above the toe, rather than at the crest or base. Advanced Simulation Framework: The novel 3D digital twin approach improves computational efficiency and enables realistic landslide evolution mapping. What are the implications of the main findings? This finding offers a new perspective for future research, as the identified stress and displacement concentration zone provides a tangible focus for further investigation. Advanced Predictive Modeling: The 3D digital twin framework provides a more stable method for simulating landslides. This approach introduces a physics-driven framework, effectively addressing the lack of realistic physical parameters in conventional hazard scenario modeling.Highlights A novel 3D digital twin framework for landslides is developed using a closest-packed spherical discrete element model. The point-contact mechanism of spherical elements simplifies friction modeling and enhances computational efficiency. Steady-state slope stress exhibits a trapezoidal distribution, increasing from the surface inwards. The stress increases uniformly from 0 kPa at the surface to 210 kPa in the innermost region. What are the main findings? A sensitive zone of the landslide mass was identified in the numerical simulations. Both stress and displacement results consistently showed the highest concentration at one-tenth of the slope height above the toe, rather than at the crest or base. Advanced Simulation Framework: The novel 3D digital twin approach improves computational efficiency and enables realistic landslide evolution mapping. What are the implications of the main findings? This finding offers a new perspective for future research, as the identified stress and displacement concentration zone provides a tangible focus for further investigation. Advanced Predictive Modeling: The 3D digital twin framework provides a more stable method for simulating landslides. This approach introduces a physics-driven framework, effectively addressing the lack of realistic physical parameters in conventional hazard scenario modeling.Abstract Background: Rainfall-induced landslides are a widespread and destructive geological hazard that resist precise prediction. They pose serious threats to human lives and property, ecological stability, and socioeconomic development. Methods: To address the challenges in mitigating rainfall-induced landslides in high-altitude mountainous regions, this study proposes a digital twin framework that couples multiple physical fields and is based on the spherical discrete element method. Results: Two-dimensional simulations identify a trapezoidal stress distribution with inward-increasing stress. The stress increases uniformly from 0 kPa at the surface to 210 kPa in the interior. The crest stress remains constant at 1.8 kPa under gravity, whereas the toe stress rises from 6.5 to 14.8 kPa with the slope gradient. While the stress pattern persists post-failure, specific magnitudes alter significantly. This study pioneers a three-dimensional close-packed spherical discrete element method, achieving enhanced computational efficiency and stability through streamlined contact mechanics. Conclusions: The proposed framework utilizes point-contact mechanics to simplify friction modeling, enhancing computational efficiency and numerical stability. By integrating stress, rainfall, and seepage fields, we establish a coupled hydro-mechanical model that enables real-time digital twin mapping of landslide evolution through dynamic parameter adjustments.
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WOS关键词VON MISES STRESS ; DECISION-SUPPORT ; PREDICTION
WOS研究方向Chemistry ; Engineering ; Instruments & Instrumentation
语种英语
WOS记录号WOS:001671381900001
出版者MDPI
源URL[http://ir.igsnrr.ac.cn/handle/311030/221049]  
专题资源与环境信息系统国家重点实验室_外文论文
通讯作者Tang, Bohui
作者单位1.Yunnan Key Lab Quantitat Remote Sensing, Kunming 650093, Peoples R China;
2.Chinese Acad Sci, State Key Lab Resources & Environm Informat Syst, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China;
3.Yunnan Inst Geoenvironm Monitoring, Kunming 650216, Peoples R China
4.Kunming Univ Sci & Technol, Fac Land & Resources Engn, Kunming 650093, Peoples R China;
5.Yunnan Int Joint Lab Integrated Sky Ground Intelli, Kunming 650093, Peoples R China;
推荐引用方式
GB/T 7714		 Li, Lai,Tang, Bohui,Cai, Fangliang,et al. Digital Twin Modeling for Landslide Risk Scenarios in Mountainous Regions[J]. SENSORS,2026,26(2):421.
APA Li, Lai,Tang, Bohui,Cai, Fangliang,Wei, Lei,Zhu, Xinming,&Fan, Dong.(2026).Digital Twin Modeling for Landslide Risk Scenarios in Mountainous Regions.SENSORS,26(2),421.
MLA Li, Lai,et al."Digital Twin Modeling for Landslide Risk Scenarios in Mountainous Regions".SENSORS 26.2(2026):421.

入库方式： OAI收割

来源：地理科学与资源研究所

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