›› 2017, Vol. 38 ›› Issue (12): 3555-3564.doi: 10.16285/j.rsm.2017.12.021

• 基础理论与实验研究 • 上一篇    下一篇

基于BUS方法的无限长边坡可靠度更新

蒋水华1, 2,姚 池1,杨建华1,周创兵1   

  1. 1. 南昌大学 建筑工程学院,江西 南昌 330031; 2. 中国科学院武汉岩土力学研究所 岩土力学与工程国家重点实验室,湖北 武汉 430071
  • 收稿日期:2016-01-04 出版日期:2017-12-11 发布日期:2018-06-05
  • 通讯作者: 姚池,男,1986年生,博士,副教授,主要从事边坡渗流与稳定性分析方面的研究工作。E-mail: chi.yao@ncu.edu.cn E-mail: sjiangaa@ncu.edu.cn
  • 作者简介:蒋水华,男,1987年生,博士,讲师,主要从事岩土工程可靠度与风险分析方面的研究工作。
  • 基金资助:

    国家自然科学基金项目(No.51509125,No.51679117);岩土力学与工程国家重点实验室开放基金项目(No.Z016014);江西省自然科学基金项目(No.20171BAB206058);中国科协青年人才托举工程项目。

Reliability updating for infinite soil slopes using BUS method

JIANG Shui-hua1, 2, YAO Chi1, YANG Jian-hua1, ZHOU Chuang-bing1   

  1. 1. School of Civil Engineering and Architecture, Nanchang University, Nanchang, Jiangxi 330031, China; 2. State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics, Chinese Academy of Sciences, Wuhan, Hubei 430071, China
  • Received:2016-01-04 Online:2017-12-11 Published:2018-06-05
  • Supported by:

    This work was supported by the National Natural Science Foundation of China (51509125, 51679117), the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering (Z016014), the Jiangxi Provincial Natural Science Foundation (20171BAB206058) and the Young Talent Lift Project of China Association for Science and Technology.

摘要: 某一特定岩土场地的试验数据、监测资料和观测信息等通常十分有限,然而贝叶斯方法却可充分利用有限的场地信息克服试验数据样本量较小的不足。为有效估计有限样本条件下参数统计特征,提出了基于结构可靠度方法和贝叶斯更新(BUS)的边坡可靠度更新方法,通过融入直剪试验数据更新无限长边坡可靠度验证了提出方法的有效性,并系统探讨了岩土体参数先验信息如试验样本量、概率分布和似然函数模型对边坡可靠度更新的影响规律。结果表明:BUS方法能够考虑岩土体参数概率分布和似然函数模型的影响,融入有限的场地信息准确地估计参数统计特征和更新边坡可靠度,为解决有限样本条件下边坡可靠度更新问题提供了一条有效的途径。土体参数概率分布对边坡可靠度更新结果(参数后验均值、标准差以及更新的失效概率)具有重要的影响,基于常用的正态和对数正态分布的边坡可靠度更新结果偏于保守,相比之下,似然函数模型对边坡可靠度更新结果的影响相对较小。此外,岩土体参数不确定性和更新的边坡失效概率均随着试验样本量的增大而减小,但当样本量增大到一定程度时它们的变化不大。

关键词: 边坡可靠度, 贝叶斯更新, 子集模拟, 先验信息, 概率分布

Abstract: Generally, the test data for a specific site are very limited. However, the Bayes method can overcome the limitation of small sample size of test data. This paper aims to apply the Bayesian updating with structural reliability methods (BUS) to update the reliability of soil slopes and estimate statistics of soil properties with limited site-investigation data. The effectiveness of the proposed approach for slope reliability is demonstrated by an infinite soil slope with direct shear test. The effects of prior information of soil properties including sample size of test data, marginal probability distribution and likelihood function on the slope reliability updating are systematically investigated. The results indicate that the BUS method can accurately estimate the statistics of soil properties and update the slope reliability incorporating limited site information and the effects of probability distribution and likelihood function. The probability distribution of soil properties has a significant effect on the updated slope reliability results (e.g., posterior mean and standard deviation, updated probability of failure). It will lead to conservative estimates of the slope reliability results when the normal or lognormal distributions are used. In contrast, the likelihood function has a slight influence on the updated slope reliability. In addition, the uncertainties of soil properties and updated probability of failure decrease as the sample size of test data increases, but they will change slightly once the sample size reaches a certain value.

Key words: slope reliability, Bayesian updating, subset simulation, prior information, probability distribution

中图分类号: 

  • TU 45

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