Posterior Resolution and Structural Modification for Parameter Determination in Bayesian Model Updating

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The challenge in this kind of updation problem is first to get confidence about the parameters that are evaluated correctly using the available data and second to get information about the remaining parameters. In this work, the first issue is resolved employing the sensitivity of the modal data used for updation. Once it is fixed that which parameters are evaluated satisfactorily using the available modal data the remaining parameters are evaluated employing modal data of a virtual structure. This virtual structure is created by adding or removing some known stiffness to or from some of the stories of the original structure. A 12-story shear building is considered for the numerical illustration of the approach. Results of the study show that the present approach is an effective tool in system identification problem when only a few data is available for updation."/> <meta name="keywords" content="Bayesian statistics, Modal parameters, Eigen sensitivity, Structural modification, MCMC"/>   <meta name="dc.title" content="Posterior Resolution and Structural Modification for Parameter Determination in Bayesian Model Updating"> <meta name="citation_author" content="Kanta Prajapat"> <meta name="citation_author" content="Samit Ray-Chaudhuri"> <meta name="dc.type" content="Article"> <meta name="dc.source" content="International Journal on Cybernetics & Informatics (IJCI),Vol. 5, No. 1"> <meta name="dc.date" content="2016/2/28"> <meta name="dc.identifier" content="10.5121/ijci.2016.5118"> <meta name="dc.publisher" content="AIRCC Publishing Corporation"> <meta name="dc.rights" content="http://creativecommons.org/licenses/by/3.0/"> <meta name="dc.format" content="application/pdf"> <meta name="dc.language" content="en"> <meta name="dc.description" content="When only a few lower modes data are available to evaluate a large number of unknown parameters, it is difficult to acquire information about all unknown parameters. The challenge in this kind of updation problem is first to get confidence about the parameters that are evaluated correctly using the available data and second to get information about the remaining parameters. In this work, the first issue is resolved employing the sensitivity of the modal data used for updation. Once it is fixed that which parameters are evaluated satisfactorily using the available modal data the remaining parameters are evaluated employing modal data of a virtual structure. This virtual structure is created by adding or removing some known stiffness to or from some of the stories of the original structure. A 12-story shear building is considered for the numerical illustration of the approach. Results of the study show that the present approach is an effective tool in system identification problem when only a few data is available for updation."/> <meta name="dc.subject" content="Bayesian statistics"> <meta name="dc.subject" content="Modal parameters"> <meta name="dc.subject" content="Eigen sensitivity"> <meta name="dc.subject" content="Structural modification"> <meta name="dc.subject" content="MCMC">   <meta name="prism.publicationName" content="International Journal on Cybernetics & Informatics (IJCI),Vol. 5, No. 1"> <meta name="prism.publicationDate" content="2016/2/28"> <meta name="prism.volume" content="5"> <meta name="prism.number" content="1"> <meta name="prism.section" content="Article"> <meta name="prism.startingPage" content="193">   <meta name="citation_journal_title" content="International Journal on Cybernetics & Informatics (IJCI),Vol. 5, No. 1"> <meta name="citation_publisher" content="AIRCC Publishing Corporation"> <meta name="citation_author" content="Kanta Prajapat"> <meta name="citation_author" content="Samit Ray-Chaudhuri"> <meta name="citation_title" content="Posterior Resolution and Structural Modification for Parameter Determination in Bayesian Model Updating"> <meta name="citation_online_date" content="2016/2/28"> <meta name="citation_volume" content="5"> <meta name="citation_issue" content="1`"> <meta name="citation_firstpage" content="193"> <meta name="citation_author" content="Kanta Prajapat"> <meta name="citation_author" content="Samit Ray-Chaudhuri"> <meta name="citation_doi" content="10.5121/ijci.2016.5118"> <meta name="citation_abstract_html_url" content="https://ijcionline.com/abstract/5116ijci18"> <meta name="citation_pdf_url" content="https://aircconline.com/ijci/V5N1/5116ijci18.pdf">   <meta property="og:site_name" content="AIRCC" /> <meta property="og:type" content="article" /> <meta property="og:url" content="https://ijcionline.com/abstract/5116ijci18"/> <meta property="og:title" content="Posterior Resolution and Structural Modification for Parameter Determination in Bayesian Model Updating"> <meta property="og:description" content="When only a few lower modes data are available to evaluate a large number of unknown parameters, it is difficult to acquire information about all unknown parameters. The challenge in this kind of updation problem is first to get confidence about the parameters that are evaluated correctly using the available data and second to get information about the remaining parameters. In this work, the first issue is resolved employing the sensitivity of the modal data used for updation. Once it is fixed that which parameters are evaluated satisfactorily using the available modal data the remaining parameters are evaluated employing modal data of a virtual structure. This virtual structure is created by adding or removing some known stiffness to or from some of the stories of the original structure. A 12-story shear building is considered for the numerical illustration of the approach. 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The challenge in this kind of updation problem is first to get confidence about the parameters that are evaluated correctly using the available data and second to get information about the remaining parameters. In this work, the first issue is resolved employing the sensitivity of the modal data used for updation. Once it is fixed that which parameters are evaluated satisfactorily using the available modal data the remaining parameters are evaluated employing modal data of a virtual structure. This virtual structure is created by adding or removing some known stiffness to or from some of the stories of the original structure. A 12-story shear building is considered for the numerical illustration of the approach. Results of the study show that the present approach is an effective tool in system identification problem when only a few data is available for updation. </p> </div> </div> <div class="card"> <h5 id="about" class="brown-text text-darken-2 text-center" style="padding-bottom:0px">Keywords</h5>  <div class="card-content"> <p class="left-text" style="text-align:justify"> Bayesian statistics, Modal parameters, Eigen sensitivity, Structural modification, MCMC </p></div> </div> <div class="card-content"> <a href="https://aircconline.com/ijci/V5N1/5116ijci18.pdf" target="blank" class="btn btn-small lighten-2 cyan lig">Full Text</a>  <a href="https://ijcionline.com/vol5" class="btn btn-small lighten-2 cyan lig">Volume 5</a> </div> </div>  <div id="side-bar" class="col s12 m3"> <div id="section-main"> <br> <br> <div class="card side cyan lighten-2"> <div class="card-content"> <ul> <li class="ax waves-effect waves-light"> <a class="white-text" href="/editorial" > <i class="material-icons left">account_circle</i>Editorial Board</a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/mostcitedarticels" > <i class="material-icons left">book</i>Most Cited Articels </a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/indexing" > <i class="material-icons left">list</i>Indexing </a> <br> </li> <br> <br> <div class="divider"></div> <br> <li class="ax waves-effect waves-light"> <a class="white-text" href="/faq" > <i class="material-icons left">help</i>FAQ </a> <br> </li> <br> <br> <div class="divider"></div> <br> </div> </div> </div> </div> </div> </div> </div> </section> <br> <br> <br> <br> <div id="txtcnt"></div>  <footer class="page-footer cyan lighten-3"> <div class="nav-wrapper"> <div class="container"> <ul> <li> <a target="_blank" href="http://airccse.org/"> <img src="/img/since2008.png" alt="since2008"></a> </li> </ul> <h6> Free Open Access Conference Proceedings <br> Computer Science & Engineering - Information Technology - Information Systems</h6> </div> <div class="footer-m col m3 s12 offset-m1"> </div> <div class="social col m3 offset-m1 s12"> </div> </div> </div> <div class="col s12 m10 offset-m1"> <div class="grey darken-3 center-align"> <small class="white-text">Designed and Developed by NNN Team</small> </div> </div> </footer> </body>  <script type="text/javascript" src="https://code.jquery.com/jquery-3.2.1.min.js"></script> <script type="text/javascript" src="/js/materialize.min.js"></script> <script src="/js/search.js"></script> <script src="/js/scrolltop.js"></script> <script src="/js/popup.js"></script> <script src="/js/main.jquery.js"></script> </html>

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Posterior Resolution and Structural Modification for Parameter Determination in Bayesian Model Updating