Probabilistic evaluation of maximum dynamic traffic load effects on cable-supported bridges under actual heavy traffic loads
The traffic load has grown significantly in recent years, which might be a threat for the service safety of existing bridges. Thus, it is an urgent task to assess the actual traffic load effects on bridges, considering actual heavy traffic load instead of design traffic load. This study presents a f...
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Veröffentlicht in: | Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability Journal of risk and reliability, 2021-02, Vol.235 (1), p.108-119 |
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creator | Liu, Yang Wang, Qinyong Lu, Naiwei |
description | The traffic load has grown significantly in recent years, which might be a threat for the service safety of existing bridges. Thus, it is an urgent task to assess the actual traffic load effects on bridges, considering actual heavy traffic load instead of design traffic load. This study presents a framework for extrapolating maximum dynamic traffic load effects on large bridges using site-specific traffic monitoring data. The framework involves vehicle–bridge interaction analysis and probabilistic modelling of extreme values. The weigh-in-motion measurements of a busy highway in China were collected for stochastic traffic load modelling. Case studies of two long-span cable-supported bridge based on the weigh-in-motion measurements were conducted to demonstrate the effectiveness of the proposed framework. It is demonstrated that Rice’s level-crossing approach can capture both dynamic and probabilistic characteristics of the traffic load effects. The root-mean-square displacement of the cable-stayed bridge follows a C-type distribution, and the one for the suspension bridge follows an M-type distribution, which is associated with the first-order mode shapes of the two types of bridges. The amplification factors for the cable-stayed bridge and the suspension bridge are 5.9% and 3.6%, respectively. The numerical analysis indicates that the dynamic effect for extrapolation is weaker with the increase in bridge span length, but the effect of traffic volume growth will be more significant. |
doi_str_mv | 10.1177/1748006X20938491 |
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Thus, it is an urgent task to assess the actual traffic load effects on bridges, considering actual heavy traffic load instead of design traffic load. This study presents a framework for extrapolating maximum dynamic traffic load effects on large bridges using site-specific traffic monitoring data. The framework involves vehicle–bridge interaction analysis and probabilistic modelling of extreme values. The weigh-in-motion measurements of a busy highway in China were collected for stochastic traffic load modelling. Case studies of two long-span cable-supported bridge based on the weigh-in-motion measurements were conducted to demonstrate the effectiveness of the proposed framework. It is demonstrated that Rice’s level-crossing approach can capture both dynamic and probabilistic characteristics of the traffic load effects. The root-mean-square displacement of the cable-stayed bridge follows a C-type distribution, and the one for the suspension bridge follows an M-type distribution, which is associated with the first-order mode shapes of the two types of bridges. The amplification factors for the cable-stayed bridge and the suspension bridge are 5.9% and 3.6%, respectively. The numerical analysis indicates that the dynamic effect for extrapolation is weaker with the increase in bridge span length, but the effect of traffic volume growth will be more significant.</description><identifier>ISSN: 1748-006X</identifier><identifier>EISSN: 1748-0078</identifier><identifier>DOI: 10.1177/1748006X20938491</identifier><language>eng</language><publisher>London, England: SAGE Publications</publisher><subject>Bridge loads ; Cable-stayed bridges ; Extreme values ; Load ; Numerical analysis ; Probability theory ; Suspension bridges ; Traffic models ; Traffic volume ; Weighing in motion</subject><ispartof>Proceedings of the Institution of Mechanical Engineers. 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Part O, Journal of risk and reliability</title><description>The traffic load has grown significantly in recent years, which might be a threat for the service safety of existing bridges. Thus, it is an urgent task to assess the actual traffic load effects on bridges, considering actual heavy traffic load instead of design traffic load. This study presents a framework for extrapolating maximum dynamic traffic load effects on large bridges using site-specific traffic monitoring data. The framework involves vehicle–bridge interaction analysis and probabilistic modelling of extreme values. The weigh-in-motion measurements of a busy highway in China were collected for stochastic traffic load modelling. Case studies of two long-span cable-supported bridge based on the weigh-in-motion measurements were conducted to demonstrate the effectiveness of the proposed framework. It is demonstrated that Rice’s level-crossing approach can capture both dynamic and probabilistic characteristics of the traffic load effects. The root-mean-square displacement of the cable-stayed bridge follows a C-type distribution, and the one for the suspension bridge follows an M-type distribution, which is associated with the first-order mode shapes of the two types of bridges. The amplification factors for the cable-stayed bridge and the suspension bridge are 5.9% and 3.6%, respectively. The numerical analysis indicates that the dynamic effect for extrapolation is weaker with the increase in bridge span length, but the effect of traffic volume growth will be more significant.</description><subject>Bridge loads</subject><subject>Cable-stayed bridges</subject><subject>Extreme values</subject><subject>Load</subject><subject>Numerical analysis</subject><subject>Probability theory</subject><subject>Suspension bridges</subject><subject>Traffic models</subject><subject>Traffic volume</subject><subject>Weighing in motion</subject><issn>1748-006X</issn><issn>1748-0078</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp1kM1LxDAQxYMouK7ePQY8V5MmbZKjLH7Bgh4U9lbSZLJ2aZs1SRcX_OPtsqIoeHrDzO-9gYfQOSWXlApxRQWXhJSLnCgmuaIHaLJbZYQIefg9l4tjdBLjihAuaEkm6OMp-FrXTdvE1BgMG90OOjW-x97hTr833dBhu-11N15T0M6N2nptMTgHJkU8okbXLWRxWK99SGBxHRq7hIiH3kLA2qRBt_gV9Gb7KyKeoiOn2whnXzpFL7c3z7P7bP549zC7nmeGEZUySw2zpQGhCq50URcgNABjjkrKc8VcCZIIW-SWWcaZqaWRQlGpGDWWWmBTdLHPXQf_NkBM1coPoR9fVjkXgpe8UGKkyJ4ywccYwFXr0HQ6bCtKql3H1d-OR0u2t0S9hJ_Qf_lPG3t-Og</recordid><startdate>202102</startdate><enddate>202102</enddate><creator>Liu, Yang</creator><creator>Wang, Qinyong</creator><creator>Lu, Naiwei</creator><general>SAGE Publications</general><general>SAGE PUBLICATIONS, INC</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><orcidid>https://orcid.org/0000-0003-3812-0385</orcidid><orcidid>https://orcid.org/0000-0003-0447-6498</orcidid></search><sort><creationdate>202102</creationdate><title>Probabilistic evaluation of maximum dynamic traffic load effects on cable-supported bridges under actual heavy traffic loads</title><author>Liu, Yang ; Wang, Qinyong ; Lu, Naiwei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c309t-d1c3d6ce79549a5b5e7aee33f1814293f6e807d52d3d343cb8c87918931cd1de3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Bridge loads</topic><topic>Cable-stayed bridges</topic><topic>Extreme values</topic><topic>Load</topic><topic>Numerical analysis</topic><topic>Probability theory</topic><topic>Suspension bridges</topic><topic>Traffic models</topic><topic>Traffic volume</topic><topic>Weighing in motion</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Yang</creatorcontrib><creatorcontrib>Wang, Qinyong</creatorcontrib><creatorcontrib>Lu, Naiwei</creatorcontrib><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><jtitle>Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Yang</au><au>Wang, Qinyong</au><au>Lu, Naiwei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Probabilistic evaluation of maximum dynamic traffic load effects on cable-supported bridges under actual heavy traffic loads</atitle><jtitle>Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability</jtitle><date>2021-02</date><risdate>2021</risdate><volume>235</volume><issue>1</issue><spage>108</spage><epage>119</epage><pages>108-119</pages><issn>1748-006X</issn><eissn>1748-0078</eissn><abstract>The traffic load has grown significantly in recent years, which might be a threat for the service safety of existing bridges. Thus, it is an urgent task to assess the actual traffic load effects on bridges, considering actual heavy traffic load instead of design traffic load. This study presents a framework for extrapolating maximum dynamic traffic load effects on large bridges using site-specific traffic monitoring data. The framework involves vehicle–bridge interaction analysis and probabilistic modelling of extreme values. The weigh-in-motion measurements of a busy highway in China were collected for stochastic traffic load modelling. Case studies of two long-span cable-supported bridge based on the weigh-in-motion measurements were conducted to demonstrate the effectiveness of the proposed framework. It is demonstrated that Rice’s level-crossing approach can capture both dynamic and probabilistic characteristics of the traffic load effects. The root-mean-square displacement of the cable-stayed bridge follows a C-type distribution, and the one for the suspension bridge follows an M-type distribution, which is associated with the first-order mode shapes of the two types of bridges. The amplification factors for the cable-stayed bridge and the suspension bridge are 5.9% and 3.6%, respectively. The numerical analysis indicates that the dynamic effect for extrapolation is weaker with the increase in bridge span length, but the effect of traffic volume growth will be more significant.</abstract><cop>London, England</cop><pub>SAGE Publications</pub><doi>10.1177/1748006X20938491</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0003-3812-0385</orcidid><orcidid>https://orcid.org/0000-0003-0447-6498</orcidid></addata></record> |
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subjects | Bridge loads Cable-stayed bridges Extreme values Load Numerical analysis Probability theory Suspension bridges Traffic models Traffic volume Weighing in motion |
title | Probabilistic evaluation of maximum dynamic traffic load effects on cable-supported bridges under actual heavy traffic loads |
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