Simulation and Analysis of Cascading Hazard Based on Fluid-Soil Coupled SPH Method
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摘要:
采用一种双向耦合的SPH数值模型，精确模拟滑坡-堵江-成坝灾害链的全过程.模型以Drucker–Prager准则描述滑体大变形行为，结合混合物理论与非线性渗流拖曳力实现水土耦合.通过室内试验验证后，成功重现白格滑坡灾害链演化，模拟结果与实测高度吻合.结果表明，滑坡入水引发的涌浪及成坝过程可依据滑体速度与能量变化清晰划分阶段.量化分析显示，内摩擦角φ增大（5°~20°）导致堰塞坝长度线性减小，高度呈幂函数增长，涌浪峰值高度显著降低.涌浪峰值与滑体入水弗劳德数呈线性正相关.上述发现揭示了滑体参数对灾害链演化路径的系统性影响，为高风险山地河流域灾害预测与风险评估提供理论支撑.
Abstract:This study adopts a bidirectionally coupled SPH numerical model to accurately simulate the full evolution of a landslide-dammed lake disaster chain. The model captures large deformation of the landslide body using the Drucker-Prager criterion and achieves water–soil coupling through mixture theory and nonlinear seepage drag forces. Validated against laboratory experiments, the model successfully reproduces the Baige landslide disaster chain, with simulation results closely matching field observations. Results show that the processes of landslide motion, impulse wave generation, and dam formation can be clearly delineated by the evolution of landslide velocity and energy. Quantitative analysis reveals that increasing the internal friction angle φ from 5° to 20° leads to a linear decrease in dam length, a power-law increase in dam height, and a significant reduction in wave height. The peak wave height exhibits a linear correlation with the landslide Froude number at impact. These findings highlight the systematic influence of landslide material properties on disaster chain dynamics and offer theoretical support for hazard prediction and risk assessment in mountainous river basins.
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图 3 滑坡入水涌浪室内试验不同时刻的照片(a~e)及对应的SPH模拟结果(f~j)
Fig. 3. Photographs of the landslide-induced wave experiments at different moments(a-e) and corresponding SPH simulation results (f-j)
图 4 不同监测点下模拟得到的浪高与试验数据对比
Fig. 4. Comparison of simulated wave heights with experimental data at different monitoring points
图 6 白格滑坡初始模型设置及监测点分布
Fig. 6. Initial model configuration and monitoring points of the Baige landslide
图 8 白格滑坡SPH模拟结果与现场调查结果对比
Fig. 8. Comparison between SPH results and field data of Baige landslide
图 11 不同内摩角φ下的堆积形态(a~d)、动能随时间演化(e)及堰塞坝长度l和高度h的定量拟合(f)
Fig. 11. Accumulation morphology (a-d), kinetic energy evolution (e), and fitting lines of the dam length l and height h (f) under varying friction angles φ
图 12 不同内摩角φ下的入水特征(a~d)、测点W3处浪高变化(e)及涌浪峰值Hmax与弗劳德数Fr的定量拟合(f)
Fig. 12. Water entry characteristics under different internal friction angles φ (a-d), wave height variation at measurement point W3 (e), and quantitative fitting of surge peak values with the Froude number Fr (f)
表 1 滑坡涌浪试验的参数设置
Table 1. Parameters of landslide-induced wave experiment
参数 值 土体颗粒密度($ \mathrm{k}\mathrm{g}/{\mathrm{m}}^{3} $) 2 500 土体杨氏模量$ (\mathrm{M}\mathrm{P}\mathrm{a} $) 5.84 土体泊松比 0.3 土体内摩擦角$ (° $) 23.3 土体粘聚力$ \left(\mathrm{P}\mathrm{a}\right) $ 20 土体中值粒径$ (m $) $ 4\times {10}^{-3} $ 土体初始体积分数 0.6 土体粒子初始间距(m) 0.01 水体密度($ \mathrm{k}\mathrm{g}/{\mathrm{m}}^{3} $) 1 000 水体动力粘度$ (\mathrm{P}\mathrm{a}\cdot \mathrm{s} $) 10-3 水体粒子初始间距(m) 0.005 
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表 2 白格滑坡的数值模型参数设置
Table 2. Parameters of Baige landslide simulation
参数 值 土体颗粒密度($ \mathrm{k}\mathrm{g}/{\mathrm{m}}^{3} $) 2 400 土体杨氏模量$ (\mathrm{M}\mathrm{P}\mathrm{a} $) 5.84 土体泊松比 0.3 土体内摩擦角$ (° $) 10.5 土体粘聚力$ \left(\mathrm{P}\mathrm{a}\right) $ 15 000 土体中值粒径$ (m $) 0.02 土体初始体积分数 0.75 土体粒子初始间距(m) 10 水体密度($ \mathrm{k}\mathrm{g}/{\mathrm{m}}^{3} $) 1 000 水体动力粘度$ (\mathrm{P}\mathrm{a}\cdot \mathrm{s} $) 10-3 水体粒子初始间距(m) 10
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