土钉边坡系统可靠度分析

IF 4.4 2区工程技术 Q1 ENGINEERING, MECHANICAL

Engineering Failure Analysis Pub Date : 2025-04-17 DOI:10.1016/j.engfailanal.2025.109613

Jie Zhang , Chen Luo , Chenguang Wu , Meng Lu , Di Wu

{"title":"土钉边坡系统可靠度分析","authors":"Jie Zhang , Chen Luo , Chenguang Wu , Meng Lu , Di Wu","doi":"10.1016/j.engfailanal.2025.109613","DOIUrl":null,"url":null,"abstract":"<div><div>Soil nails are extensively employed to improve slope stability. It is exceedingly difficult to analyze the reliability for a soil-nailed slope because there are numerous possible slip surfaces (SSs) and different rows of soil nails may have several different failure modes (FMs). This paper suggests a response surface methodology utilizing backpropagation neural network to assess system reliability (SR) of soil-nailed slope. To evaluate SR for soil-nailed slopes, this research proposes a response surface approach built on backpropagation neural network. How to analyze the most critical FMs govern SR of soil-nailed slope is also described. The recommended method is illustrated with an example of a soil-nailed slope. It is discovered that SR of soil-nailed slope is commonly dominated by a few representative failure modes (RFMs). Furthermore, the SR of slope increases with the number of nail rows when the soil nails are subjected to tensile failure. It also increases with the nail length when soil nails are subjected to pullout failure or deep failure. This study offers practical methods and valuable insights for the SR analysis and design of soil-nailed slopes.</div></div>","PeriodicalId":11677,"journal":{"name":"Engineering Failure Analysis","volume":"176 ","pages":"Article 109613"},"PeriodicalIF":4.4000,"publicationDate":"2025-04-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"System reliability analysis of soil-nailed slopes\",\"authors\":\"Jie Zhang , Chen Luo , Chenguang Wu , Meng Lu , Di Wu\",\"doi\":\"10.1016/j.engfailanal.2025.109613\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Soil nails are extensively employed to improve slope stability. It is exceedingly difficult to analyze the reliability for a soil-nailed slope because there are numerous possible slip surfaces (SSs) and different rows of soil nails may have several different failure modes (FMs). This paper suggests a response surface methodology utilizing backpropagation neural network to assess system reliability (SR) of soil-nailed slope. To evaluate SR for soil-nailed slopes, this research proposes a response surface approach built on backpropagation neural network. How to analyze the most critical FMs govern SR of soil-nailed slope is also described. The recommended method is illustrated with an example of a soil-nailed slope. It is discovered that SR of soil-nailed slope is commonly dominated by a few representative failure modes (RFMs). Furthermore, the SR of slope increases with the number of nail rows when the soil nails are subjected to tensile failure. It also increases with the nail length when soil nails are subjected to pullout failure or deep failure. This study offers practical methods and valuable insights for the SR analysis and design of soil-nailed slopes.</div></div>\",\"PeriodicalId\":11677,\"journal\":{\"name\":\"Engineering Failure Analysis\",\"volume\":\"176 \",\"pages\":\"Article 109613\"},\"PeriodicalIF\":4.4000,\"publicationDate\":\"2025-04-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Failure Analysis\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1350630725003541\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, MECHANICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Failure Analysis","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1350630725003541","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}

引用次数: 0

摘要

土钉广泛用于提高边坡稳定性。土钉边坡的可靠度分析是非常困难的，因为存在许多可能的滑移面，并且不同排的土钉可能有几种不同的破坏模式。本文提出了一种基于反向传播神经网络的响应面方法来评估土钉支护边坡的系统可靠度。为了评估土钉边坡的SR，本文提出了一种基于反向传播神经网络的响应面方法。本文还介绍了如何分析控制土钉边坡SR的最关键FMs。并以土钉边坡为例进行了说明。研究发现，土钉边坡的SR通常由几种具有代表性的破坏模式（rfm）控制。土钉受拉破坏时，边坡的SR随土钉排数的增加而增大。土钉发生拉拔破坏或深部破坏时，土钉抗拔强度随钉长增加而增大。该研究为土钉边坡的SR分析和设计提供了实用的方法和有价值的见解。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

System reliability analysis of soil-nailed slopes

Soil nails are extensively employed to improve slope stability. It is exceedingly difficult to analyze the reliability for a soil-nailed slope because there are numerous possible slip surfaces (SSs) and different rows of soil nails may have several different failure modes (FMs). This paper suggests a response surface methodology utilizing backpropagation neural network to assess system reliability (SR) of soil-nailed slope. To evaluate SR for soil-nailed slopes, this research proposes a response surface approach built on backpropagation neural network. How to analyze the most critical FMs govern SR of soil-nailed slope is also described. The recommended method is illustrated with an example of a soil-nailed slope. It is discovered that SR of soil-nailed slope is commonly dominated by a few representative failure modes (RFMs). Furthermore, the SR of slope increases with the number of nail rows when the soil nails are subjected to tensile failure. It also increases with the nail length when soil nails are subjected to pullout failure or deep failure. This study offers practical methods and valuable insights for the SR analysis and design of soil-nailed slopes.

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

Engineering Failure Analysis 工程技术-材料科学：表征与测试

CiteScore

7.70

自引率

20.00%

发文量

956

审稿时长

47 days

期刊介绍： Engineering Failure Analysis publishes research papers describing the analysis of engineering failures and related studies. Papers relating to the structure, properties and behaviour of engineering materials are encouraged, particularly those which also involve the detailed application of materials parameters to problems in engineering structures, components and design. In addition to the area of materials engineering, the interacting fields of mechanical, manufacturing, aeronautical, civil, chemical, corrosion and design engineering are considered relevant. Activity should be directed at analysing engineering failures and carrying out research to help reduce the incidences of failures and to extend the operating horizons of engineering materials. Emphasis is placed on the mechanical properties of materials and their behaviour when influenced by structure, process and environment. Metallic, polymeric, ceramic and natural materials are all included and the application of these materials to real engineering situations should be emphasised. The use of a case-study based approach is also encouraged. Engineering Failure Analysis provides essential reference material and critical feedback into the design process thereby contributing to the prevention of engineering failures in the future. All submissions will be subject to peer review from leading experts in the field.