考虑非线性蠕变的露天矿边坡预警阈值确定

Determination of early warning threshold for open-pit slope considering nonlinear creep

  • 摘要: 露天矿边坡监测作为保障人员与设备安全的最后一道防线,其核心在于构建精准的预警阈值. 当前我国露天矿边坡监测系统存在预警阈值设定缺乏系统性和阈值确定缺乏科学理论支撑的问题. 对此,本研究提出基于蠕变理论的预警方法:围绕蠕变曲线发展规律与累计位移量变化特征,通过解析边坡蠕变三阶段的临界位移比例关系来确定预警值. 基于矿区代表性岩石力学参数,通过PFC3D离散元模拟构建简化岩体模型,进行常三轴压缩试验获取应力–应变曲线,反演得到用于蠕变方程的本构参数(弹性模量和黏度系数),再建立蠕变方程推导出位移比例关系式. 基于模拟的蠕变曲线得出方程所需的关键点及三级蠕变的起点值,并引入锁固段破坏机制概念和重正化群理论量化空间变异影响,推导临界位移阈值,进而求出蠕变演化的四级预警值,并与露天矿C现场GNSS监测的累计位移数据进行对比,验证预警阈值的准确性. 对于突发的异常变形,引入切线角判据完善预警机制. 试验表明,以露天矿C预警阈值为例,蠕变发出Ⅰ级预警(6216 mm)至滑坡发生提前了11.6天,之后进行短期的变形速率预警阈值监测,当变形速率发出Ⅰ级预警(97.2 mm·d−1)后3小时发生滑坡. 通过长短周期预警的协同作用,提升了预警系统的准确性和可靠性.

     

    Abstract: Stability monitoring of the open-pit slope is the last key line of defense for ensuring the safety of mine personnel and integrity of production equipment. Setting scientific, accurate, and reliable early warning thresholds can enhance monitoring effectiveness. However, the current open-pit slope monitoring system in China is lacking in scientific theoretical support and methodology in setting early warning thresholds. To address this problem, this study proposes an innovative method for constructing early warning thresholds based on slope creep theory. The core idea of this method is to deeply explore the internal development law of the slope creep curve, especially the evolution characteristics of cumulative displacement with time. The research focuses on the three classic stages of the slope creep process (initial, steady state, and accelerated). The displacement ratio, determined by an analysis of the critical point between the three stages, can be used as a key scientific basis in determining and grading warning thresholds. First, the representative rock mass mechanical parameters of the target open-pit mine C were selected, and a simplified rock mass model, which can reflect the key structural characteristics, was constructed using three-dimensional (3D) particle flow code (PFC) discrete element numerical simulation software. The stress–strain curves of rock mass under different stress levels were obtained via a numerical simulation of a conventional triaxial compression test. Based on the simulated stress–strain curves and creep theory, the key parameters of the constitutive equation describing the creep behavior of rock mass—namely, the elastic modulus and viscosity coefficient—were determined. Additionally, the concept of the locking segment failure mechanism was introduced, and renormalization group theory was applied to quantify the influence of the spatial variability of rock mass on macro strength and deformation. The creep proportional relationship was combined with locked segment theory and the quantitative results of spatial variability to derive a critical displacement threshold, which is more in line with the actual geological conditions. Based on the evolution characteristics of the critical displacement threshold and creep curve, thresholds for a four-level early warning system were determined to provide a hierarchical response basis for different stages of deformation. To verify the accuracy and practicability of the proposed method, the derived early warning thresholds were compared with the long-term cumulative displacement data obtained by the mine site monitoring global navigation satellite system (GNSS). The results show that the threshold constructed based on creep theory can effectively capture the key deformation stage before slope instability. Taking open-pit mine C as an example, the creep theory early warning based on cumulative displacement sent an alarm when the Level I early warning threshold (6216 mm) was reached, 11.6 days ahead of the final landslide occurrence time, providing a valuable time window for emergency response and personnel and equipment evacuation. At the short-term acceleration stage near the landslide, the landslide occurred only 3 h after the Level I warning threshold (97.2 mm) triggered by the deformation rate (tangent angle criterion), capturing the rapid acceleration process before the final instability. The accuracy and reliability of the early warning system were improved through the synergy of long- and short-term early warning mechanisms.

     

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