Probabilistic deterioration modeling of bridge component condition with random effects

Milhan Moomen, C. Siddiqui
{"title":"Probabilistic deterioration modeling of bridge component condition with random effects","authors":"Milhan Moomen, C. Siddiqui","doi":"10.1080/24705314.2022.2048244","DOIUrl":null,"url":null,"abstract":"ABSTRACT Timely maintenance of bridge components is critical for bridge management functions. With reliable deterioration models, highway agencies can efficiently allocate funding for bridge maintenance and customize maintenance schedules to meet agency budgets. The increased public expectation of acceptable levels of service for bridges coupled with other competing needs makes it crucially important to accurately estimate bridge future conditions so that adequate resources may be allocated for repair and reconstruction purposes. Accurately predicting bridge condition is challenging due to the inherent random nature of factors impacting deterioration, the existence of unobserved variables that are not measured, panel nature of the data and the effects of bridge-specific correlation. Without accounting for these factors, the resulting estimated deterioration models may have biased and inconsistent parameter estimates. This article assembled a comprehensive set of bridge and climate data from the National Bridge Inventory (NBI) and the South Carolina Climatology office. Bridge component deterioration models for bridges on state highways in South Carolina were estimated using an ordered probit model with random effects specification to account for the randomness and panel nature of the bridge data. The study results are useful for various bridge management tasks including maintenance programming, budgeting and bridge asset evaluation.","PeriodicalId":43844,"journal":{"name":"Journal of Structural Integrity and Maintenance","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2022-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Structural Integrity and Maintenance","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1080/24705314.2022.2048244","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
引用次数: 5

Abstract

ABSTRACT Timely maintenance of bridge components is critical for bridge management functions. With reliable deterioration models, highway agencies can efficiently allocate funding for bridge maintenance and customize maintenance schedules to meet agency budgets. The increased public expectation of acceptable levels of service for bridges coupled with other competing needs makes it crucially important to accurately estimate bridge future conditions so that adequate resources may be allocated for repair and reconstruction purposes. Accurately predicting bridge condition is challenging due to the inherent random nature of factors impacting deterioration, the existence of unobserved variables that are not measured, panel nature of the data and the effects of bridge-specific correlation. Without accounting for these factors, the resulting estimated deterioration models may have biased and inconsistent parameter estimates. This article assembled a comprehensive set of bridge and climate data from the National Bridge Inventory (NBI) and the South Carolina Climatology office. Bridge component deterioration models for bridges on state highways in South Carolina were estimated using an ordered probit model with random effects specification to account for the randomness and panel nature of the bridge data. The study results are useful for various bridge management tasks including maintenance programming, budgeting and bridge asset evaluation.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
随机影响下桥梁构件状态的概率劣化建模
及时维护桥梁构件对桥梁管理功能至关重要。有了可靠的老化模型,公路机构可以有效地分配桥梁维修资金,并定制维修计划以满足机构预算。公众对桥梁可接受的服务水平的期望越来越高,再加上其他相互竞争的需求,这使得准确估计桥梁未来的状况变得至关重要,以便为修复和重建目的分配足够的资源。由于影响恶化的因素具有固有的随机性,存在未测量的未观察变量,数据的面板性质以及桥梁特定相关性的影响,因此准确预测桥梁状况具有挑战性。如果不考虑这些因素,估计的退化模型可能有偏差和不一致的参数估计。本文收集了一套全面的桥梁和气候数据,这些数据来自国家桥梁清单(NBI)和南卡罗来纳州气候学办公室。为了考虑桥梁数据的随机性和面板性质,使用随机效应规范的有序probit模型估计了南卡罗来纳州州际公路桥梁部件退化模型。研究结果可用于各种桥梁管理工作,包括维修规划、预算编制和桥梁资产评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
3.90
自引率
9.50%
发文量
24
期刊最新文献
Influential factor analysis of slag-based engineered cementitious composites using Taguchi robust method Influence of corrosion-based section loss on morphology and tensile capacity of pre-stressing strands Application of electrical resistivity for estimating compressive strength of FRC at early-ages Evaluation and optimization of volume fraction and aspect ratio of Polyethylene Terephthalate (PET) fibers in self-compacting lightweight concrete Vulnerability assessment of tall isolated steel building under variable earthquake hazard levels using endurance time method
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1