刘勇锋, 张超.基于多源传感监测的大型尾矿库溃坝物理模拟及冲击影响研究[J].河南理工大学学报（自然科学版）,2025,44(6):64-74.

LIU Y F, ZHANG C.Physical simulation and impact analysis of large-scale tailings dam reach based on multi-dource densing monitoring[J].Journal of Henan Polytechnic University(Natural Science) ,2025,44(6):64-74.

基于多源传感监测的大型尾矿库溃坝物理模拟及冲击影响研究

刘勇锋1,2, 张超3

1.重庆大学 资源与安全学院，重庆  400044；2.深圳市中金岭南有色金属股份有限公司，广东 深圳  518024；3.中国科学院武汉岩土力学研究所 岩土力学与工程安全全国重点实验室，湖北 武汉  430071

摘要: 目的 为了深入探究大型尾矿库极端工况下溃坝过程中孔隙水压力、土压力的动态演化规律以及下泄尾砂流的冲击特性和运动行为，为高势能尾矿库风险评估与安全防控提供科学依据。  方法 以广东某大型山谷型尾矿库为原型，基于几何相似比1∶100构建高精度室内物理模型，并创新性地集成了多源传感监测系统。试验模拟了500年一遇极端降雨引发洪水漫顶导致的溃坝情景，并系统记录从蓄水、漫顶、溃口形成扩展到最终失稳的完整过程。  结果 结果表明：（1）孔隙水压力呈“蓄水阶段阶梯上升、溃决阶段骤降、消散阶段缓慢降低”的三阶段演化特征，坝体附近孔压消散速率较库尾快40%；（2）土压力变化在坝体前部区域响应剧烈，峰值达13.6 kPa后线性衰减，中后部保持稳定，反映出溃口影响范围的空间非均匀性；（3）溃流量与泥沙瞬时剥离量呈非线性正相关关系，最大溃流量达240万m³，相当于原型总库容的48.7%，溃口峰值流速2.6 m/s；（4）下泄尾砂流流速分布受地形粗糙度控制，沟道中部流速呈“驼峰形”，泄流量增大时演变为“双驼峰形”，垂直沟道流速符合“中间快、两侧慢”特征，涡量峰值与地形粗糙度正相关。 结论 研究提出的“双驼峰流速模型”揭示了复杂地形条件下尾矿浆体下泄的流态特征与涡量演变规律，为尾矿库下游灾害范围预测、冲击力评估和防护工程设计提供了新的理论工具与技术支撑。

关键词:尾矿坝;物理模拟;多源传感监测;溃流动力学;双驼峰流速模型

doi:10.16186/j.cnki.1673-9787.2025030071

基金项目:国家重点研发计划项目（2023YFC3012200）

收稿日期:2025/03/29

修回日期:2025/05/28

出版日期:2025/10/14

Physical simulation and impact analysis of large-scale tailings dam reach based on multi-dource densing monitoring

Liu Yongfeng1,2, Zhang Chao3

1.College of Resources and Safety Engineering， Chongqing University， Chongqing  400044， China；2.Shenzhen Zhongjin Lingnan Nonferrous Metals Co.， Ltd.， Shenzhen  518024， Guangdong， China；3.State Key Laboratory of Geomechanics and Geotechnical Engineering Safety， Institute of Rock and Soil Mechanics， Chinese Academy of Sciences， Wuhan  430071， Hubei， China

Abstract: Objectives An investigation is conducted into the dynamic evolution of pore water pressure and earth pressure during dam breaching in large tailings reservoirs under extreme conditions， as well as the impact characteristics and kinematics of released tailings flow， to establish a scientific basis for risk assessment and safety control of high-potential-energy tailings reservoirs. Methods Using a large valley-type tailings reservoir in Guangdong as the prototype， a high-precision indoor physical model with a geometric similarity ratio of 1∶100 was constructed， and a multi-source sensing and monitoring system was innovatively integrated. The experiment simulated a dam-breach scenario induced by extreme rainfall with a 500-year return period leading to overtopping， and systematically recorded the entire process from impoundment and overtopping through breach initiation and enlargement to eventual failure. Results The results indicate that： （1） Pore water pressure exhibits a three-phase evolution pattern： stepwise increase during impoundment， abrupt drop during breaching， and gradual decrease during the dissipation -with the dissipation rate near the dam being 40% faster than at the the reservoir tail. （2） Earth pressure responds most strongly in the fore-dam region， reaching a peak of 13.6 kPa before decaying linearly， while remaining stable in the middle and rear sections， indicating spatial non-uniformity in the breach influence zone. （3） Breach discharge is nonlinearly and positively correlated with the instantaneous sediment detachment. The maximum breach volume reached 2.4 million m³， equivalent to 48.7% of the prototype’s total storage， with a peak breach velocity of 2.6 m/s. （4） The velocity distribution of the released tailings flow is controlled by terrain roughness： mid-channel velocity shows a “hump-shaped” profile， which evolves into a “double-hump” pattern with increasing discharge； transverse to the channel， the velocity is “fast in the center， slow on the sides” and peak vorticity is positively correlated with terrain roughness.  Conclusions The proposed “double-hump velocity model” reveals the flow regime and vorticity evolution of tailings slurry release under complex topography， offering a new theoretical tool and technical support for predicting downsteam hazard extent， assessing impact forces， and designing protective works for tailings reservoirs.

Key words: tailings dam; physical simulation; multi-source sensing and monitoring; breach flow dynamics; double-hump velocity model