基于随机损伤模型和布尔分布的结构内混凝土强度随机模型

IF 5.7 1区 工程技术 Q1 ENGINEERING, CIVIL
Jingran He , Junjie Hong , Ruofan Gao , Jinju Tao , Hongmin Yan
{"title":"基于随机损伤模型和布尔分布的结构内混凝土强度随机模型","authors":"Jingran He ,&nbsp;Junjie Hong ,&nbsp;Ruofan Gao ,&nbsp;Jinju Tao ,&nbsp;Hongmin Yan","doi":"10.1016/j.strusafe.2024.102443","DOIUrl":null,"url":null,"abstract":"<div><p>The probability measure of low-quality concrete is essential for the reliability analysis of concrete structures. However, this problem is usually neglected, and the normal distribution or lognormal distribution is often selected as the probability distribution of concrete strength. In this study, a better solution for this problem is given by theoretically deriving of the Burr distribution based on the stochastic damage model. A large amount of in-situ test data in engineering structures is applied to perform a K-S test of different distribution types and to fit the distribution parameters. As a result, the advantage of Burr distribution in representing the tail probability is explained by both theoretical derivation and fitting results. And the Burr distribution is accepted by the K-S test in every strength grade while the other distribution types are all partly rejected.</p></div>","PeriodicalId":21978,"journal":{"name":"Structural Safety","volume":"108 ","pages":"Article 102443"},"PeriodicalIF":5.7000,"publicationDate":"2024-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Stochastic modelling of in-structure concrete strength based on stochastic damage model and Burr distribution\",\"authors\":\"Jingran He ,&nbsp;Junjie Hong ,&nbsp;Ruofan Gao ,&nbsp;Jinju Tao ,&nbsp;Hongmin Yan\",\"doi\":\"10.1016/j.strusafe.2024.102443\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The probability measure of low-quality concrete is essential for the reliability analysis of concrete structures. However, this problem is usually neglected, and the normal distribution or lognormal distribution is often selected as the probability distribution of concrete strength. In this study, a better solution for this problem is given by theoretically deriving of the Burr distribution based on the stochastic damage model. A large amount of in-situ test data in engineering structures is applied to perform a K-S test of different distribution types and to fit the distribution parameters. As a result, the advantage of Burr distribution in representing the tail probability is explained by both theoretical derivation and fitting results. And the Burr distribution is accepted by the K-S test in every strength grade while the other distribution types are all partly rejected.</p></div>\",\"PeriodicalId\":21978,\"journal\":{\"name\":\"Structural Safety\",\"volume\":\"108 \",\"pages\":\"Article 102443\"},\"PeriodicalIF\":5.7000,\"publicationDate\":\"2024-01-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Structural Safety\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167473024000146\",\"RegionNum\":1,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Structural Safety","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167473024000146","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 0

摘要

低质量混凝土的概率度量对于混凝土结构的可靠性分析至关重要。然而,这一问题通常被忽视,通常选择正态分布或对数正态分布作为混凝土强度的概率分布。本研究基于随机损伤模型,从理论上推导出 Burr 分布,为这一问题提供了更好的解决方案。应用工程结构中的大量现场测试数据,对不同分布类型进行 K-S 检验,并拟合分布参数。因此,理论推导和拟合结果都解释了 Burr 分布在表示尾部概率方面的优势。通过 K-S 检验,Burr 分布在每个强度等级中都被接受,而其他分布类型都被部分拒绝。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stochastic modelling of in-structure concrete strength based on stochastic damage model and Burr distribution

The probability measure of low-quality concrete is essential for the reliability analysis of concrete structures. However, this problem is usually neglected, and the normal distribution or lognormal distribution is often selected as the probability distribution of concrete strength. In this study, a better solution for this problem is given by theoretically deriving of the Burr distribution based on the stochastic damage model. A large amount of in-situ test data in engineering structures is applied to perform a K-S test of different distribution types and to fit the distribution parameters. As a result, the advantage of Burr distribution in representing the tail probability is explained by both theoretical derivation and fitting results. And the Burr distribution is accepted by the K-S test in every strength grade while the other distribution types are all partly rejected.

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
Structural Safety
Structural Safety 工程技术-工程:土木
CiteScore
11.30
自引率
8.60%
发文量
67
审稿时长
53 days
期刊介绍: Structural Safety is an international journal devoted to integrated risk assessment for a wide range of constructed facilities such as buildings, bridges, earth structures, offshore facilities, dams, lifelines and nuclear structural systems. Its purpose is to foster communication about risk and reliability among technical disciplines involved in design and construction, and to enhance the use of risk management in the constructed environment
×
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