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姬建, 王乐沛, 廖文旺, 张卫杰, 朱德胜, 高玉峰. 基于WUS概率密度权重法的边坡稳定系统可靠度分析[J]. 岩土工程学报, 2021, 43(8): 1492-1501. DOI: 10.11779/CJGE202108014
引用本文: 姬建, 王乐沛, 廖文旺, 张卫杰, 朱德胜, 高玉峰. 基于WUS概率密度权重法的边坡稳定系统可靠度分析[J]. 岩土工程学报, 2021, 43(8): 1492-1501. DOI: 10.11779/CJGE202108014
JI Jian, WANG Le-pei, LIAO Wen-wang, ZHANG Wei-jie, ZHU De-sheng, GAO Yu-feng. System reliability analysis of slopes based on weighted uniform simulation method[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(8): 1492-1501. DOI: 10.11779/CJGE202108014
Citation: JI Jian, WANG Le-pei, LIAO Wen-wang, ZHANG Wei-jie, ZHU De-sheng, GAO Yu-feng. System reliability analysis of slopes based on weighted uniform simulation method[J]. Chinese Journal of Geotechnical Engineering, 2021, 43(8): 1492-1501. DOI: 10.11779/CJGE202108014

基于WUS概率密度权重法的边坡稳定系统可靠度分析

System reliability analysis of slopes based on weighted uniform simulation method

  • 摘要: 复杂边坡工程中由于边坡土体分层或土体参数的不确定性等因素,边坡失稳往往会发生在多个潜在失稳滑面,因此,采用单一临界确定性滑面或临界概率滑面对边坡系统可靠度进行分析会极大低估其失效概率。运用WUS(Weighted Uniform Simulation)方法对边坡系统可靠度进行了概率分析,运用4个多层边坡算例演示WUS对于边坡系统可靠度分析的良好适用性。分析结果表明,该方法对高维、隐式极限状态方程下的多层土边坡问题分析精度较高的同时,可极大减少边坡模型计算样本数,例如,对于边坡可靠度分析MCS通常需要104以上的样本量,而WUS仅需500组左右即可满足精度要求。通过对原始WUS算法的修正,在样本量足够的情况下,修正WUS法能更加高效计算得到复杂边坡系统失效概率,并且可以自动摒弃冗余失效模式而得到较为准确的多失效模式所对应的多组可靠度参数设计点,即MPP(Most Probable Failure Point),进而高效识别出多层土复杂边坡的代表性滑动面,为边坡安全及失稳灾害防治提供重要的参考价值。

     

    Abstract: In practical engineering, due to the slope stratification or the spatial variability of soil properties, the slope will often fail along multiple potential sliding surfaces. Considering that using a single critical deterministic sliding surface or a critical probability sliding surface to analyze slope reliability will greatly underestimate the probability of failure, this study uses the weighted uniform simulation (WUS) method to analyze the system reliability of slopes. Four multi-layer slope cases are used to prove that the WUS has good applicability for system reliability analysis of slopes. High accuracy is obtained for multi-layer slope problems under high-dimensional and implicit limit state equations by this method, while the sample size is greatly reduced from 104 samples required by the direct Monte Carlo simulation to only about 500 samples under the same accuracy requirements. By modifying the original WUS algorithm, when the sample size is sufficient, the modified WUS can efficiently obtain the system failure probability and effectively abandon redundant failure modes to obtain accurate most probable failure points corresponding to multiple failure modes. Furthermore, the representative sliding surfaces of the multi-layer slope can be effectively and automatically identified, which provides important reference value for the later maintenance and failure prevention of slopes.

     

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