基于多源试验数据空间变异土体参数概率反演及边坡可靠度更新  

Probabilistic back analysis of spatially varying soil properties and reliability updating of slopes with multiple sources of test data

作　　者：蒋水华[1] 魏博文[1] 张文举[2] 江先河 黄劲松[1] JIANG Shui-hua;WEI Bo-wen;ZHANG Wen-ju;JIANG Xian-he;HUANG Jin-song(School of Civil Engineering and Architecture, Nanchang University, Nanchang, Jiangxi 330031, China;Hunan Lishui Hydro ＆ Power Co., Ltd., Changsha,Hunan 410014, China;Jiangxi Water Resources Institute, Nanchang, Jiangxi 330013, China)

机构地区：[1]南昌大学建筑工程学院,江西南昌330031 [2]湖南澧水流域水利水电开发有限责任公司,湖南长沙410014 [3]江西水利职业学院,江西南昌330013

出　　处：《岩土力学》2018年第4期1491-1499,共9页Rock and Soil Mechanics

基　　金：国家自然科学基金项目(No.51509125;No.51679117;No.U1765207);江西省水利科技计划项目(No.KT201534);江西省自然科学基金项目(No.20171BAB206058)~~

摘　　要：岩土工程现场勘察试验通常只能获得有限的试验数据,据此难以真实地量化土体参数的空间变异性。提出了考虑土体参数空间变异性的概率反演和边坡可靠度更新方法,基于室内和现场两种不同来源的试验数据概率反演空间变异参数统计特征和更新边坡可靠度水平,并给出了计算流程。此外为合理地描述土体参数先验信息,发展了不排水抗剪强度非平稳随机场模型。最后通过不排水饱和黏土边坡算例验证了提出方法的有效性,并探讨了试验数据和钻孔位置对边坡后验失效概率的影响。结果表明:提出方法实现了空间变异土体参数概率反演与边坡可靠度更新的一体化,基于有限的多源试验数据概率反演得到的土体参数均值与试验数据非常吻合,明显降低了对参数不确定性的估计,更新的边坡可靠度水平显著增加。受土体参数空间自相关性的影响,试验数据对钻孔取样点附近区域土体参数统计特征更新的影响明显大于距离取样点较远区域。In general, limited test data can be collected from geotechnical site investigation. However, it is typically difficult to accurately characterize the spatial variation in soil properties with limited test data. This paper aims to propose a probabilistic back analysis and reliability updating approach considering the spatial variability of soil properties. With this approach, multiple sources of test data including laboratory and in situ test data can be utilized to rationally back analyze the spatially varying soil properties and update the slope reliability. The implementation procedures of the proposed approach are presented step by step. In addition, a non-stationary random field model of undrained shear strength is developed for proper characterization of the prior information of soil property. Finally, a clay slope under undrained conditions is investigated to demonstrate the effectiveness of the proposed approach. The influences of the test data and borehole location on the posterior probability of slope failure are also addressed. The results indicate that the proposed approach can effectively back analyze the spatially varying soil properties and update the slope reliability. By incorporating multiple sources of test data into the Bayesian analysis, the estimated means of soil parameters are consistent with the test data. The uncertainties of soil parameters are greatly reduced and the slope reliability is significantly improved. Due to spatial variation, test data has a stronger effect on the updating of soil parameter statistics with short distances to the borehole locations of measurement, compared with soil parameter statistics with long distances to the borehole locations.

关 键 词：边坡可靠度 空间变异性 非平稳随机场 概率反演 贝叶斯更新 

分 类 号：TU45[建筑科学—岩土工程]