边坡稳定性强度折减颗粒离散元法分析的细观参数标定策略

根据岩土体力学指标标定颗粒细观参数是应用颗粒离散元解决岩土工程问题的一项基础工作。用颗粒离散元法执行边坡稳定性强度折减法分析时,岩土体抗剪强度随折减系数变化不断调整,使用试算法标定颗粒细观参数则效率严重不足。为解决此问题,采用国产颗粒离散元软件MatDEM,以颗粒细观参数为输入、岩土体抗剪强度指标为输出构建BP神经网络,开发双轴压缩数值模型并行试验技术加速神经网络样本数据的获取过程,重复执行“逆向标定-精度检查-样本修正”实现颗粒细观参数的逆向迭代修正标定。测试试验结果表明,该策略标定的颗粒细观参数与抗剪强度目标高度匹配,数值试验结果与目标值相比误差可控制在不超过1%。采用澳大利亚计算机应用协会（ACADS）的两个边坡稳定性分析经典考题,以模型平均位移突变为极限状态判据执行强度折减法分析,检验该策略的应用效果。结果显示：该策略的标定能力可满足抗剪强度不断调整时颗粒细观参数重新设定的需要,安全系数计算结果与ACADS推荐解具有良好可比性。

Calibration of Micro Parameters of Particles in Granular Discrete Element Method to Assess Slope Stability by Strength Reduction Method

Calibration of micro parameters of particles based on the mechanical properties of rock and soil mass is essential to solve various geotechnical problems by using granular discrete element method. If strength reduction method is employed in granular discrete element method to assess slope stability, the shear strength of rock and soil mass will be continuously adjusted according to the reduction factor, and then, micro parameters of particles should be constantly calibrated. In this case, the trial and error method is cumbersome and time consuming. To solve the issue, take MatDEM as an example, BP neural network is built by setting micro parameters of particles as input and the shear strength of rock and soil mass as output. And, a technique is developed to carry out biaxial compression numerical tests in parallel. Then, a reverse-iterative-correct strategy is proposed to calibrate micro parameters of particles for a prescribed value of shear strength, by executing the "reversely determination-error check-sample correction" process repeatedly. Results of numerical tests verified that micro parameters obtained by the new strategy have a remarkable precision. The relative error between the prescribed values and the numerical test results is less than one percent. Two exam problems suggested by ACADS are adopted to verify the ability of the proposed strategy in slope stability analysis based on strength reduction method. Results show that the new strategy satisfies the calibration requirement on micro parameters of particles when executing strength reduction method in MatDEM and the resulted safe factors agree with the safe factors recommended by ACADS.