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    Bridge Performance Monitoring Based on Traffic Data

    Source: Journal of Engineering Mechanics:;2013:;Volume ( 139 ):;issue: 011
    Author:
    André D.
    ,
    Orcesi
    ,
    Dan M.
    ,
    Frangopol
    DOI: 10.1061/(ASCE)EM.1943-7889.0000582
    Publisher: American Society of Civil Engineers
    Abstract: There is a huge interest in developing new performance metrics, based on monitoring information and considering uncertainties in the resistance and loading effects, to be used by stakeholders when determining maintenance and rehabilitation strategies for existing bridges. The cost of structural health monitoring is generally a criterion in the duration of the monitoring program, and determining when, and how long, monitoring can be interrupted is still a challenge. Providing an approach that quantifies the benefits of monitoring is crucial for stakeholders. The objective of this paper is threefold: build a performance indicator based on monitoring information that considers uncertainties and correlation in recorded data; use this indicator to check and predict if serviceability and safety thresholds are reached; and analyze the impact of short monitoring interruptions on the performance assessment accuracy by balancing cost of monitoring with the efficiency of the results. The originality of the proposed approach consists in the introduction of a performance indicator in the structural reliability analysis, based on monitoring programs. The regression methodology enables one to apply the reliability analysis when monitoring is interrupted during short-term periods and to assess the impact of such interruptions on the structural analysis accuracy. The proposed approach is applied on an existing bridge.
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      Bridge Performance Monitoring Based on Traffic Data

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/61072
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    • Journal of Engineering Mechanics

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    contributor authorAndré D.
    contributor authorOrcesi
    contributor authorDan M.
    contributor authorFrangopol
    date accessioned2017-05-08T21:44:11Z
    date available2017-05-08T21:44:11Z
    date copyrightNovember 2013
    date issued2013
    identifier other%28asce%29em%2E1943-7889%2E0000591.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/61072
    description abstractThere is a huge interest in developing new performance metrics, based on monitoring information and considering uncertainties in the resistance and loading effects, to be used by stakeholders when determining maintenance and rehabilitation strategies for existing bridges. The cost of structural health monitoring is generally a criterion in the duration of the monitoring program, and determining when, and how long, monitoring can be interrupted is still a challenge. Providing an approach that quantifies the benefits of monitoring is crucial for stakeholders. The objective of this paper is threefold: build a performance indicator based on monitoring information that considers uncertainties and correlation in recorded data; use this indicator to check and predict if serviceability and safety thresholds are reached; and analyze the impact of short monitoring interruptions on the performance assessment accuracy by balancing cost of monitoring with the efficiency of the results. The originality of the proposed approach consists in the introduction of a performance indicator in the structural reliability analysis, based on monitoring programs. The regression methodology enables one to apply the reliability analysis when monitoring is interrupted during short-term periods and to assess the impact of such interruptions on the structural analysis accuracy. The proposed approach is applied on an existing bridge.
    publisherAmerican Society of Civil Engineers
    titleBridge Performance Monitoring Based on Traffic Data
    typeJournal Paper
    journal volume139
    journal issue11
    journal titleJournal of Engineering Mechanics
    identifier doi10.1061/(ASCE)EM.1943-7889.0000582
    treeJournal of Engineering Mechanics:;2013:;Volume ( 139 ):;issue: 011
    contenttypeFulltext
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