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  <doc>
    <id>57449</id>
    <completedYear/>
    <publishedYear>2023</publishedYear>
    <thesisYearAccepted/>
    <language>eng</language>
    <pageFirst>1</pageFirst>
    <pageLast>27</pageLast>
    <pageNumber/>
    <edition/>
    <issue/>
    <volume/>
    <type>article</type>
    <publisherName>Wiley</publisherName>
    <publisherPlace>Hoboken, NJ</publisherPlace>
    <creatingCorporation/>
    <contributingCorporation/>
    <belongsToBibliography>1</belongsToBibliography>
    <completedDate>--</completedDate>
    <publishedDate>--</publishedDate>
    <thesisDateAccepted>--</thesisDateAccepted>
    <title language="eng">Bayesian model calibration and damage detection for a digital twin of a bridge demonstrator</title>
    <abstract language="eng">Using digital twins for decision making is a very promising concept which combines simulation models with corresponding experimental sensor data in order to support maintenance decisions or to investigate the reliability. The quality of the prognosis strongly depends on both the data quality and the quality of the digital twin. The latter comprises both the modeling assumptions as well as the correct parameters of these models. This article discusses the challenges when applying this concept to realmeasurement data for a demonstrator bridge in the lab, including the data management, the iterative development of the simulation model as well as the identification/updating procedure using Bayesian inference with a potentially large number of parameters. The investigated scenarios include both the iterative identification of the structural model parameters as well as scenarios related to a damage identification. In addition, the article aims at providing all models and data in a reproducibleway such that other researcher can use this setup to validate their methodologies.</abstract>
    <parentTitle language="eng">Engineering reports</parentTitle>
    <identifier type="doi">10.1002/eng2.12669</identifier>
    <identifier type="issn">2577-8196</identifier>
    <identifier type="urn">urn:nbn:de:kobv:b43-574496</identifier>
    <enrichment key="opus.source">publish</enrichment>
    <enrichment key="date_peer_review">22.05.2023</enrichment>
    <enrichment key="PaperofMonth">1</enrichment>
    <licence>Creative Commons - CC BY - Namensnennung 4.0 International</licence>
    <author>Thomas Titscher</author>
    <author>T. van Dijk</author>
    <author>Daniel Kadoke</author>
    <author>Annika Robens-Radermacher</author>
    <author>Ralf Herrmann</author>
    <author>Jörg F. Unger</author>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Damage detection</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Finite element analysis</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Load identification</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Model updating</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Estimation</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>System identification</value>
    </subject>
    <subject>
      <language>eng</language>
      <type>uncontrolled</type>
      <value>Variational Bayesian statistics</value>
    </subject>
    <collection role="institutes" number="">7 Bauwerkssicherheit</collection>
    <collection role="institutes" number="">7.2 Ingenieurbau</collection>
    <collection role="institutes" number="">8 Zerstörungsfreie Prüfung</collection>
    <collection role="institutes" number="">8.1 Sensorik, mess- und prüftechnische Verfahren</collection>
    <collection role="themenfelder" number="">Infrastruktur</collection>
    <collection role="literaturgattung" number="">Verlagsliteratur</collection>
    <collection role="fulltextaccess" number="">Datei für die Öffentlichkeit verfügbar ("Open Access")</collection>
    <collection role="unnumberedseries" number="">Wissenschaftliche Artikel der BAM</collection>
    <collection role="institutes" number="">7.7 Modellierung und Simulation</collection>
    <thesisPublisher>Bundesanstalt für Materialforschung und -prüfung (BAM)</thesisPublisher>
    <file>https://opus4.kobv.de/opus4-bam/files/57449/2023_Titscher_Bayesian model calibration and damage detection for a digital twin of a bridge.pdf</file>
  </doc>
</export-example>
