考虑土壤性质非平稳特征的降雨条件下边坡破坏机理贝叶斯反分析及可靠性评估

IF 3.3 2区 工程技术 Q2 ENGINEERING, GEOLOGICAL
Xian Liu , Shui-Hua Jiang , Jiawei Xie , Xueyou Li
{"title":"考虑土壤性质非平稳特征的降雨条件下边坡破坏机理贝叶斯反分析及可靠性评估","authors":"Xian Liu ,&nbsp;Shui-Hua Jiang ,&nbsp;Jiawei Xie ,&nbsp;Xueyou Li","doi":"10.1016/j.sandf.2025.101568","DOIUrl":null,"url":null,"abstract":"<div><div>Slope failure mechanism and reliability assessment under rainfall usually not only ignores the nonstationary characteristics of soil hydraulic and shear strength parameters, but also does not make use of the freely available field observation that the slope remains stable under the natural condition. In this paper, the nonstationary characteristics and spatial variabilities of soil hydraulic and shear strength parameters, along with model bias, are explicitly accounted for. Firstly, Bayesian inverse analysis is conducted to infer the spatially varying shear strength parameters and reduce their uncertainties by incorporating the field observation. Following this, an infinite slope model is taken as an example to perform slope seepage, stability and reliability analyses subjected to a rainfall event based on the posterior statistics of soil shear strength parameters. The probabilities of slope failure and distributions of critical slip surface for various rainfall durations are then evaluated within a Monte-Carlo simulation framework. Based on these, the slope failure mechanism induced solely by the rainfall is investigated. The results indicate that the probability of failure of the infinite slope, when evaluated using the posterior statistics of soil shear strength parameters, is close to zero (7.24 × 10<sup>−2</sup>), which aligns with the field observation wherein the slope remains stable under the natural condition. The triggering factors for slope failure vary across different stages of rainfall infiltration are identified and elucidated in this paper. Ignoring the field observation and the nonstationary characteristics of soil properties can lead to inaccurate assessments of both the failure mechanisms and probabilities of slopes induced by the rainfall. The research can provide a new perspective for understanding the slope failure mechanism caused by the rainfall.</div></div>","PeriodicalId":21857,"journal":{"name":"Soils and Foundations","volume":"65 1","pages":"Article 101568"},"PeriodicalIF":3.3000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties\",\"authors\":\"Xian Liu ,&nbsp;Shui-Hua Jiang ,&nbsp;Jiawei Xie ,&nbsp;Xueyou Li\",\"doi\":\"10.1016/j.sandf.2025.101568\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Slope failure mechanism and reliability assessment under rainfall usually not only ignores the nonstationary characteristics of soil hydraulic and shear strength parameters, but also does not make use of the freely available field observation that the slope remains stable under the natural condition. In this paper, the nonstationary characteristics and spatial variabilities of soil hydraulic and shear strength parameters, along with model bias, are explicitly accounted for. Firstly, Bayesian inverse analysis is conducted to infer the spatially varying shear strength parameters and reduce their uncertainties by incorporating the field observation. Following this, an infinite slope model is taken as an example to perform slope seepage, stability and reliability analyses subjected to a rainfall event based on the posterior statistics of soil shear strength parameters. The probabilities of slope failure and distributions of critical slip surface for various rainfall durations are then evaluated within a Monte-Carlo simulation framework. Based on these, the slope failure mechanism induced solely by the rainfall is investigated. The results indicate that the probability of failure of the infinite slope, when evaluated using the posterior statistics of soil shear strength parameters, is close to zero (7.24 × 10<sup>−2</sup>), which aligns with the field observation wherein the slope remains stable under the natural condition. The triggering factors for slope failure vary across different stages of rainfall infiltration are identified and elucidated in this paper. Ignoring the field observation and the nonstationary characteristics of soil properties can lead to inaccurate assessments of both the failure mechanisms and probabilities of slopes induced by the rainfall. The research can provide a new perspective for understanding the slope failure mechanism caused by the rainfall.</div></div>\",\"PeriodicalId\":21857,\"journal\":{\"name\":\"Soils and Foundations\",\"volume\":\"65 1\",\"pages\":\"Article 101568\"},\"PeriodicalIF\":3.3000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Soils and Foundations\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0038080625000022\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, GEOLOGICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Soils and Foundations","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038080625000022","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, GEOLOGICAL","Score":null,"Total":0}
引用次数: 0

摘要

降雨作用下边坡破坏机理及可靠度评估往往忽略了土体水力和抗剪强度参数的非平稳特性,也没有充分利用自然条件下边坡稳定的现场观测资料。本文明确考虑了土体水力和抗剪强度参数的非平稳特征和空间变异性,以及模型偏差。首先,通过贝叶斯反分析,结合现场观测,推断出抗剪强度参数的空间变化规律,降低其不确定性;在此基础上,以无限边坡模型为例,基于土体抗剪强度参数后验统计,进行降雨作用下边坡渗流、稳定性和可靠度分析。然后在蒙特卡罗模拟框架内评估不同降雨持续时间的边坡破坏概率和临界滑移面分布。在此基础上,对降雨单独引起的边坡破坏机理进行了研究。结果表明,利用土抗剪强度参数后验统计进行评估时,无限边坡的破坏概率接近于零(7.24 × 10−2),这与现场观测结果一致,其中边坡在自然条件下保持稳定。本文对降雨入渗不同阶段引起边坡破坏的触发因素进行了识别和阐述。忽略现场观测和土壤性质的非平稳特征,可能导致对降雨引起的边坡破坏机制和概率的不准确评估。该研究为认识降雨引起的边坡失稳机理提供了新的视角。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian inverse analysis with field observation for slope failure mechanism and reliability assessment under rainfall accounting for nonstationary characteristics of soil properties
Slope failure mechanism and reliability assessment under rainfall usually not only ignores the nonstationary characteristics of soil hydraulic and shear strength parameters, but also does not make use of the freely available field observation that the slope remains stable under the natural condition. In this paper, the nonstationary characteristics and spatial variabilities of soil hydraulic and shear strength parameters, along with model bias, are explicitly accounted for. Firstly, Bayesian inverse analysis is conducted to infer the spatially varying shear strength parameters and reduce their uncertainties by incorporating the field observation. Following this, an infinite slope model is taken as an example to perform slope seepage, stability and reliability analyses subjected to a rainfall event based on the posterior statistics of soil shear strength parameters. The probabilities of slope failure and distributions of critical slip surface for various rainfall durations are then evaluated within a Monte-Carlo simulation framework. Based on these, the slope failure mechanism induced solely by the rainfall is investigated. The results indicate that the probability of failure of the infinite slope, when evaluated using the posterior statistics of soil shear strength parameters, is close to zero (7.24 × 10−2), which aligns with the field observation wherein the slope remains stable under the natural condition. The triggering factors for slope failure vary across different stages of rainfall infiltration are identified and elucidated in this paper. Ignoring the field observation and the nonstationary characteristics of soil properties can lead to inaccurate assessments of both the failure mechanisms and probabilities of slopes induced by the rainfall. The research can provide a new perspective for understanding the slope failure mechanism caused by the rainfall.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Soils and Foundations
Soils and Foundations 工程技术-地球科学综合
CiteScore
6.40
自引率
8.10%
发文量
99
审稿时长
5 months
期刊介绍: Soils and Foundations is one of the leading journals in the field of soil mechanics and geotechnical engineering. It is the official journal of the Japanese Geotechnical Society (JGS)., The journal publishes a variety of original research paper, technical reports, technical notes, as well as the state-of-the-art reports upon invitation by the Editor, in the fields of soil and rock mechanics, geotechnical engineering, and environmental geotechnics. Since the publication of Volume 1, No.1 issue in June 1960, Soils and Foundations will celebrate the 60th anniversary in the year of 2020. Soils and Foundations welcomes theoretical as well as practical work associated with the aforementioned field(s). Case studies that describe the original and interdisciplinary work applicable to geotechnical engineering are particularly encouraged. Discussions to each of the published articles are also welcomed in order to provide an avenue in which opinions of peers may be fed back or exchanged. In providing latest expertise on a specific topic, one issue out of six per year on average was allocated to include selected papers from the International Symposia which were held in Japan as well as overseas.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信