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    考虑多参数空间变异性的非饱和土石坝坝坡可靠度分析

    Reliability Analysis of Unsaturated Earth-Rock Dam Slope Considering Multi-Parameter Spatial Variability

    • 摘要: 准确地进行非饱和土石坝坝坡可靠度分析需综合考虑土体抗剪强度参数和水力参数的空间变异性.这种多参数问题常因随机场离散的变量过多而造成维度灾难,传统分析方法难以适用.为此,提出了一种基于分片逆回归(SIR)的多元自适应回归样条(MARS)土石坝坝坡可靠度分析方法.该方法采用SIR降维,经降维后的变量矩阵通过MARS构建代理模型,进而采用蒙特卡洛模拟(MCS)评估土石坝坝坡失效概率.以某一土石坝为例,验证了所提方法的有效性,并探讨了计算结果随各参数空间变异性的变化规律,分析了滑坡规模与频率间的关系.研究结果表明:抗剪强度参数变异性对坝坡失效概率的影响大于水力参数变异性的影响;所提方法在各参数变异系数变化的情况下都能得出准确的计算结果,并有效地降低计算成本;该方法可为高维及小失效概率非饱和土石坝坝坡可靠度问题提供一条有效的途径.

       

      Abstract: Accurate slope reliability analysis of unsaturated earth and rock dams requires a combination of spatial variability in soil shear strength parameters and hydraulic parameters.Such multi-parameter problems often result in dimensional catastrophes due to too many variables discrete from the random field,and traditional analysis methods are difficult to apply.For this reason,the multivariate adaptive regression spline (MARS) method based on sliced inverse regression (SIR) is proposed to analyze the slope reliability of earth and rock dams.The method uses SIR to reduce the dimensionality,and the reduced variable matrix is used to construct surrogate models by MARS,and then Monte Carlo simulation (MCS) is used to evaluate the probability of failure of earth-rock dam slopes.The validity of the proposed method is verified by taking an earth and rock dam as an example,and the variation rule of the calculation results with the spatial variability of each parameter is explored,and the relationship between landslide magnitude and frequency is analyzed.The results indicate that the effect of shear strength parameter variability on dam slope failure probability is larger than that of hydraulic parameter variability;the proposed method can produce accurate calculation results under the variation of the coefficients of variation of each parameter and effectively reduce the cost of calculation;the method can provide an effective way to solve the problem of slope reliability of unsaturated earth and rock dams with high dimensionality and small failure probability.

       

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