A new GPU-accelerated coupled discrete element and depth-averaged model for simulation of flow-like landslides
A new GPU-accelerated coupled discrete element and depth-averaged model for simulation of flow-like landslides
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DOI：
10.1016/j.envsoft.2022.105412
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发表时间：
2022-07
期刊：
影响因子：
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通讯作者：
Xiaoli Su;Q. Liang;X. Xia
中科院分区：
文献类型：
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作者：
Xiaoli Su;Q. Liang;X. Xia
水流式山体滑坡是一种常见的自然灾害，可能对人员及其财产造成巨大风险。已经报道了模拟流状滑坡的不同模型，但由于基本假设和简化，所有这些模型都具有局限性。利用两种主流建模方法的优点，开发了一种新的耦合模型，该模型采用离散元法（DEM）模型来模拟源区的复杂塌陷过程，并采用深度平均模型（DAM）来预测跳动区和沉积区的主要对流运动。耦合模型最终在NVIDIA CUDA编程平台上实现，实现GPU高性能计算。考虑进行两次实验室测试来验证该模型，并模拟现场规模的滑坡事件以验证其在现实条件下的适用性。令人满意的结果证实耦合模型能够再现现实世界中流状滑坡的动态过程。
Flow-like landslides are a common type of natural hazards that may impose a great risk to people and their properties. Different models have been reported for simulating flow-like landslides, all of which possess limitations due to the underlying assumptions and simplifications. Harnessing the advantages of two types of prevailing modelling approaches, a new coupled model is developed which adopts a discrete element method (DEM) model to simulate the complex collapsing process in the source area and a depth-averaged model (DAM) to predict the predominantly convective movement in the runout and deposition zones. The coupled model is finally implemented on the NVIDIA CUDA programming platform to achieve GPU high-performance computing. Two laboratory tests are considered to validate the model and a field-scale landslide event is simulated to verify its applicability in real-world conditions. Satisfactory results confirm that the coupled model is able to reproduce the dynamic process of real-world flow-like landslides.