Rapid evaluation of drivers’ ride comfort on long-span suspension bridges under VIV using Gaussian process regression

IF 4.2 2区 工程技术 Q1 ENGINEERING, CIVIL Journal of Wind Engineering and Industrial Aerodynamics Pub Date : 2025-02-26 DOI:10.1016/j.jweia.2025.106060
Han Li , Ziluo Xiong , Jin Zhu , Longwei Ma , Yongle Li , Zongyu Gao
{"title":"Rapid evaluation of drivers’ ride comfort on long-span suspension bridges under VIV using Gaussian process regression","authors":"Han Li ,&nbsp;Ziluo Xiong ,&nbsp;Jin Zhu ,&nbsp;Longwei Ma ,&nbsp;Yongle Li ,&nbsp;Zongyu Gao","doi":"10.1016/j.jweia.2025.106060","DOIUrl":null,"url":null,"abstract":"<div><div>Vortex-induced vibration (VIV) significantly affects ride comfort and may necessitate traffic restrictions, disrupting economic and social activities. The combined impact of VIV and traffic on ride comfort is not well understood, and existing studies are often too time-consuming for timely bridge management decisions. This study aims to explore ride comfort on long-span suspension bridges (LSSBs) during VIV and develop an online prediction model for real-time evaluations, aiding bridge management decisions. A vortex-traffic-bridge (VTB) simulation platform is established to extract vehicle dynamic responses and calculate motion sickness incidence (MSI) for evaluating ride comfort during VIV. MSI is treated probabilistically due to traffic flow's stochastic nature. The optimal probabilistic distribution model (PDM) for MSI data is identified using Jensen-Shannon divergence. A Gaussian process regression (GPR) surrogate model is constructed with VIV mode, VIV amplitude, and traffic density as inputs, and PDM parameters for MSI as outputs. A case study of a prototype LSSB using the GPR surrogate model thoroughly investigates the influence of VIV mode, VIV amplitude, and traffic density on MSI. This model can timely predict drivers' MSI under VIV, aiding effective bridge management decisions.</div></div>","PeriodicalId":54752,"journal":{"name":"Journal of Wind Engineering and Industrial Aerodynamics","volume":"260 ","pages":"Article 106060"},"PeriodicalIF":4.2000,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Wind Engineering and Industrial Aerodynamics","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S016761052500056X","RegionNum":2,"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

Abstract

Vortex-induced vibration (VIV) significantly affects ride comfort and may necessitate traffic restrictions, disrupting economic and social activities. The combined impact of VIV and traffic on ride comfort is not well understood, and existing studies are often too time-consuming for timely bridge management decisions. This study aims to explore ride comfort on long-span suspension bridges (LSSBs) during VIV and develop an online prediction model for real-time evaluations, aiding bridge management decisions. A vortex-traffic-bridge (VTB) simulation platform is established to extract vehicle dynamic responses and calculate motion sickness incidence (MSI) for evaluating ride comfort during VIV. MSI is treated probabilistically due to traffic flow's stochastic nature. The optimal probabilistic distribution model (PDM) for MSI data is identified using Jensen-Shannon divergence. A Gaussian process regression (GPR) surrogate model is constructed with VIV mode, VIV amplitude, and traffic density as inputs, and PDM parameters for MSI as outputs. A case study of a prototype LSSB using the GPR surrogate model thoroughly investigates the influence of VIV mode, VIV amplitude, and traffic density on MSI. This model can timely predict drivers' MSI under VIV, aiding effective bridge management decisions.
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
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
8.90
自引率
22.90%
发文量
306
审稿时长
4.4 months
期刊介绍: The objective of the journal is to provide a means for the publication and interchange of information, on an international basis, on all those aspects of wind engineering that are included in the activities of the International Association for Wind Engineering http://www.iawe.org/. These are: social and economic impact of wind effects; wind characteristics and structure, local wind environments, wind loads and structural response, diffusion, pollutant dispersion and matter transport, wind effects on building heat loss and ventilation, wind effects on transport systems, aerodynamic aspects of wind energy generation, and codification of wind effects. Papers on these subjects describing full-scale measurements, wind-tunnel simulation studies, computational or theoretical methods are published, as well as papers dealing with the development of techniques and apparatus for wind engineering experiments.
期刊最新文献
Rapid evaluation of drivers’ ride comfort on long-span suspension bridges under VIV using Gaussian process regression Editorial Board Identification of flow regimes and dispersion pathways around in-line cylinders Cladding pressure and load characteristics of a tall building under a simulated tornado-like vortex: An experimental study Sensitivity analysis of wavy wall performance in turbulent separation control: Effects of amplitude and period variations
×
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