考虑场地相似性的小样本边坡可靠度分析  

Reliability analysis of slopes from sparse measurements considering sites similarity

作　　者：许领 王文龙 赵腾远 XU Ling;WANG Wenlong;ZHAO Tengyuan(School of Human Settlements and Civil Engineering,Xi'an Jiaotong University,Xi'an,Shaanxi 710000,China)

机构地区：[1]西安交通大学人居环境与建筑工程学院,陕西西安710000

出　　处：《岩石力学与工程学报》2025年第4期977-988,共12页Chinese Journal of Rock Mechanics and Engineering

基　　金：国家自然科学基金资助项目(42107204)。

摘　　要：针对小样本条件下岩土试验数据统计不确定性大、岩土体参数概率分布不准确、边坡可靠度分析不合理的问题,通过综合考虑多个工程场地的相似特点,使用分层贝叶斯模型(HBM),充分借助相似工程场地的数据信息,并结合马尔科夫链蒙特卡洛(MCMC),实现小样本条件下目标场地岩土参数多维概率分布的合理刻画。采用陕北多个黄土工程场地的真实c,?数据,验证HBM方法对于小样本条件下构建岩土参数概率分布的有效性。并在此基础上,开展某黄土边坡的可靠度分析。结果表明:与独立参数模型(IPM)(不考虑相似工程场地数据信息)相比,HBM对应的边坡失效概率从11.6%降低到4.8%。此外,为了进一步验证HBM的相较传统方法的准确性,还通过大量模拟数据进行试验。结果表明:相比于IPM而言,HBM所得结果准确度能够提升33%~53%,不确定性降低19%~53%。This paper proposes a hierarchical Bayesian method(HBM)combined with Markov Chain Monte Carlo(MCMC)to address the challenges of large statistical uncertainty in geotechnical experimental data,inaccurate probability distribution of geotechnical parameters,and unreasonable slope reliability analysis under small samplesized conditions.The HBM comprehensively incorporates information from multiple similar geotechnical sites and integrates it with the limited measurements from the target site.This approach enables a more reasonable characterization of the probability distribution of geotechnical parameters under small sample conditions.The proposed method is validated using real datasets from several loess sites in northern Shaanxi Province,China.Based on these datasets,a reliability analysis of a loess slope is conducted to demonstrate the practical application of the HBM.The results indicate that,compared to the independent parameter model(IPM),which does not utilize information from similar geotechnical sites,the failure probability of the loess slope is reduced from 11.6%to 4.8%when using the HBM.Additionally,extensive numerical simulations are carried out to further verify the accuracy of the HBM compared to traditional methods.The results show that,compared to IPM,the HBM improves the accuracy of geotechnical statistics by 33%to 53%and reduces uncertainty by approximately 19%to 53%.

关 键 词：土力学 土体参数的概率分布 贝叶斯方法 分层贝叶斯模型 可靠度理论 

分 类 号：TU43[建筑科学—岩土工程]