{"title":"基于上界法的空间可变土壤挖掘稳定性概率分析","authors":"","doi":"10.1016/j.compgeo.2024.106769","DOIUrl":null,"url":null,"abstract":"<div><p>The limit analysis incorporated with the random field theorem is an effective approach for the probabilistic analysis of geotechnical engineering stability. A failure mechanism for excavation stability analysis in spatially variable soil, which is combined with random field theory with rotational failure mechanism of excavation is proposed. Random distribution of soil shear strength parameters is readily generated with the proposed approach, thereby enabling efficient and accurate estimation of the failure probability of an excavation. Through an illustrative example, the feasibility of combining random field with rotational failure mechanism is verified. Through several practical engineering cases, the rationality of probability analysis results is verified. Parametric sensitivity analysis is performed with Monte Carlo method to investigate the effects of each factor on the failure probability of an excavation in spatially variable soil. The results show that the proposed failure mechanism of excavation in spatially variable soil provides the reasonable failure probability calculation results for engineering practices.</p></div>","PeriodicalId":55217,"journal":{"name":"Computers and Geotechnics","volume":null,"pages":null},"PeriodicalIF":5.3000,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Probabilistic analysis for excavation stability in spatially variable soil based on upper bound method\",\"authors\":\"\",\"doi\":\"10.1016/j.compgeo.2024.106769\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The limit analysis incorporated with the random field theorem is an effective approach for the probabilistic analysis of geotechnical engineering stability. A failure mechanism for excavation stability analysis in spatially variable soil, which is combined with random field theory with rotational failure mechanism of excavation is proposed. Random distribution of soil shear strength parameters is readily generated with the proposed approach, thereby enabling efficient and accurate estimation of the failure probability of an excavation. Through an illustrative example, the feasibility of combining random field with rotational failure mechanism is verified. Through several practical engineering cases, the rationality of probability analysis results is verified. Parametric sensitivity analysis is performed with Monte Carlo method to investigate the effects of each factor on the failure probability of an excavation in spatially variable soil. The results show that the proposed failure mechanism of excavation in spatially variable soil provides the reasonable failure probability calculation results for engineering practices.</p></div>\",\"PeriodicalId\":55217,\"journal\":{\"name\":\"Computers and Geotechnics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.3000,\"publicationDate\":\"2024-09-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers and Geotechnics\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0266352X24007080\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Geotechnics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0266352X24007080","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Probabilistic analysis for excavation stability in spatially variable soil based on upper bound method
The limit analysis incorporated with the random field theorem is an effective approach for the probabilistic analysis of geotechnical engineering stability. A failure mechanism for excavation stability analysis in spatially variable soil, which is combined with random field theory with rotational failure mechanism of excavation is proposed. Random distribution of soil shear strength parameters is readily generated with the proposed approach, thereby enabling efficient and accurate estimation of the failure probability of an excavation. Through an illustrative example, the feasibility of combining random field with rotational failure mechanism is verified. Through several practical engineering cases, the rationality of probability analysis results is verified. Parametric sensitivity analysis is performed with Monte Carlo method to investigate the effects of each factor on the failure probability of an excavation in spatially variable soil. The results show that the proposed failure mechanism of excavation in spatially variable soil provides the reasonable failure probability calculation results for engineering practices.
期刊介绍:
The use of computers is firmly established in geotechnical engineering and continues to grow rapidly in both engineering practice and academe. The development of advanced numerical techniques and constitutive modeling, in conjunction with rapid developments in computer hardware, enables problems to be tackled that were unthinkable even a few years ago. Computers and Geotechnics provides an up-to-date reference for engineers and researchers engaged in computer aided analysis and research in geotechnical engineering. The journal is intended for an expeditious dissemination of advanced computer applications across a broad range of geotechnical topics. Contributions on advances in numerical algorithms, computer implementation of new constitutive models and probabilistic methods are especially encouraged.