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    Seismic Fragility Evaluation with Incomplete Structural Appraisal Data: An Iterative Statistical Approach

    Source: Journal of Structural Engineering:;2014:;Volume ( 140 ):;issue: 002
    Author:
    Vincent Z. Wang
    ,
    Michael Mallett
    ,
    Andrew Priory
    DOI: 10.1061/(ASCE)ST.1943-541X.0000804
    Publisher: American Society of Civil Engineers
    Abstract: This paper presents an iterative statistical approach to evaluating seismic structural safety using incomplete appraisal data. Despite the continuous improvement to traditional structural assessment procedures and the recent progress in structural health monitoring methodologies, practically acquired structural appraisal data may often be incomplete. The occurrence of the appraisal data missingness could be ascribed to the malfunction of data acquisition systems, the abnormality during data transfer, and the inaccessibility of critical quantities, among other reasons. The study begins with a quantitative investigation into the sensitivity of the seismic fragility evaluation with respect to the structural appraisal data missingness through the defined additional information loss and probability of noninformativeness. Subsequently, a remedy for the missingness of the structural appraisal data, instead of a precaution against it, is formulated by employing the expectation-maximization (EM) algorithm. With synthetic or real seismic ground accelerations involved, the efficacy of the EM algorithm embedded remedy is demonstrated by examples of typical linear or nonlinear hysteretic systems in the framework of statistical hypothesis testing. Resorting to the bootstrap technique, the influence of the related correlations and missingness probability is also examined.
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      Seismic Fragility Evaluation with Incomplete Structural Appraisal Data: An Iterative Statistical Approach

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    http://yetl.yabesh.ir/yetl1/handle/yetl/68738
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    contributor authorVincent Z. Wang
    contributor authorMichael Mallett
    contributor authorAndrew Priory
    date accessioned2017-05-08T22:00:42Z
    date available2017-05-08T22:00:42Z
    date copyrightFebruary 2014
    date issued2014
    identifier other%28asce%29st%2E1943-541x%2E0000846.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/68738
    description abstractThis paper presents an iterative statistical approach to evaluating seismic structural safety using incomplete appraisal data. Despite the continuous improvement to traditional structural assessment procedures and the recent progress in structural health monitoring methodologies, practically acquired structural appraisal data may often be incomplete. The occurrence of the appraisal data missingness could be ascribed to the malfunction of data acquisition systems, the abnormality during data transfer, and the inaccessibility of critical quantities, among other reasons. The study begins with a quantitative investigation into the sensitivity of the seismic fragility evaluation with respect to the structural appraisal data missingness through the defined additional information loss and probability of noninformativeness. Subsequently, a remedy for the missingness of the structural appraisal data, instead of a precaution against it, is formulated by employing the expectation-maximization (EM) algorithm. With synthetic or real seismic ground accelerations involved, the efficacy of the EM algorithm embedded remedy is demonstrated by examples of typical linear or nonlinear hysteretic systems in the framework of statistical hypothesis testing. Resorting to the bootstrap technique, the influence of the related correlations and missingness probability is also examined.
    publisherAmerican Society of Civil Engineers
    titleSeismic Fragility Evaluation with Incomplete Structural Appraisal Data: An Iterative Statistical Approach
    typeJournal Paper
    journal volume140
    journal issue2
    journal titleJournal of Structural Engineering
    identifier doi10.1061/(ASCE)ST.1943-541X.0000804
    treeJournal of Structural Engineering:;2014:;Volume ( 140 ):;issue: 002
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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