Uncertainty assessment for the Bayesian updating process of concrete strength properties
Reassessment of infrastructure buildings has become an essential approach to deal with increasing traffic loads on ageing infrastructure buildings and to verify the service-life of those structures. Good estimation of the actual material properties is highly relevant for reliable structural reassess...
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Czech Technical University in Prague
2022-08-01
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| Series: | Acta Polytechnica CTU Proceedings |
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| Online Access: | https://ojs.cvut.cz/ojs/index.php/APP/article/view/8370 |
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| author | Matthias Haslbeck Robert Kroyer Andreas Taras Thomas Braml |
| author_facet | Matthias Haslbeck Robert Kroyer Andreas Taras Thomas Braml |
| author_sort | Matthias Haslbeck |
| collection | DOAJ |
| description | Reassessment of infrastructure buildings has become an essential approach to deal with increasing traffic loads on ageing infrastructure buildings and to verify the service-life of those structures. Good estimation of the actual material properties is highly relevant for reliable structural reassessment. Although this holds for all building materials, the importance of good parameter estimation is of special importance for concrete structures, where the strength properties show relatively high variation and where the nominal strength properties tend to be too conservative. Modern design guidelines allow to make use of scientific methods such as Bayesian Updating of material properties to enable a more realistic consideration of the actual material properties in the reassessment of existing structures. However, guidelines for application and experience with those methods are not yet reported much or are rather vague [1]. The presented study focuses on the effect of the Bayesian Updating process for material parameters with special emphasis on the number and sampling location of test specimens as well as on the accuracy and confidence in the obtained posterior distribution, since sampling also includes a certain margin of uncertainty. The investigation on the methodological potential and on the uncertainty margin in the updating process in this contribution uses a batch of 14 test results on the concrete compressive strength obtained from drill cores along with the inherent measurement uncertainties from the testing procedure. After a short review of Bayes’ Theorem, the Markov Chain Monte Carlo Method (MCMC) and the bootstrap methodology, all combinations of subsamples of size 1, 3 and 5 specimens were built and provided to the Bayes’ updating procedure via MCMC to determine the posterior distributions. The series of obtained posterior distributions for a certain subsample was used to determine the uncertainty in the Bayesian Updating process by evaluation of the scatter in the expected value, the standard deviation and the 5 %-quantile of the updated distribution. The simulations show the importance of an adequate sample size and quantify the uncertainties arising from the limited number of observations. |
| format | Article |
| id | doaj-art-fe5bfc4f6bec45e8b90a220dc0be6641 |
| institution | DOAJ |
| issn | 2336-5382 |
| language | English |
| publishDate | 2022-08-01 |
| publisher | Czech Technical University in Prague |
| record_format | Article |
| series | Acta Polytechnica CTU Proceedings |
| spelling | doaj-art-fe5bfc4f6bec45e8b90a220dc0be66412025-08-20T02:49:20ZengCzech Technical University in PragueActa Polytechnica CTU Proceedings2336-53822022-08-0136768310.14311/APP.2022.36.00765610Uncertainty assessment for the Bayesian updating process of concrete strength propertiesMatthias Haslbeck0Robert Kroyer1Andreas Taras2Thomas Braml3University of the Bundeswehr Munich, Institute for Structural Engineering, Werner-Heisenberg-Weg 39, D-85577 Neubiberg, GermanySwiss Federal Institute of Technology Zürich (ETHZ), Institute of Structural Engineering, Stefano-Franscini-Platz 5, 8093 Zürich, SwitzerlandSwiss Federal Institute of Technology Zürich (ETHZ), Institute of Structural Engineering, Stefano-Franscini-Platz 5, 8093 Zürich, SwitzerlandUniversity of the Bundeswehr Munich, Institute for Structural Engineering, Werner-Heisenberg-Weg 39, D-85577 Neubiberg, GermanyReassessment of infrastructure buildings has become an essential approach to deal with increasing traffic loads on ageing infrastructure buildings and to verify the service-life of those structures. Good estimation of the actual material properties is highly relevant for reliable structural reassessment. Although this holds for all building materials, the importance of good parameter estimation is of special importance for concrete structures, where the strength properties show relatively high variation and where the nominal strength properties tend to be too conservative. Modern design guidelines allow to make use of scientific methods such as Bayesian Updating of material properties to enable a more realistic consideration of the actual material properties in the reassessment of existing structures. However, guidelines for application and experience with those methods are not yet reported much or are rather vague [1]. The presented study focuses on the effect of the Bayesian Updating process for material parameters with special emphasis on the number and sampling location of test specimens as well as on the accuracy and confidence in the obtained posterior distribution, since sampling also includes a certain margin of uncertainty. The investigation on the methodological potential and on the uncertainty margin in the updating process in this contribution uses a batch of 14 test results on the concrete compressive strength obtained from drill cores along with the inherent measurement uncertainties from the testing procedure. After a short review of Bayes’ Theorem, the Markov Chain Monte Carlo Method (MCMC) and the bootstrap methodology, all combinations of subsamples of size 1, 3 and 5 specimens were built and provided to the Bayes’ updating procedure via MCMC to determine the posterior distributions. The series of obtained posterior distributions for a certain subsample was used to determine the uncertainty in the Bayesian Updating process by evaluation of the scatter in the expected value, the standard deviation and the 5 %-quantile of the updated distribution. The simulations show the importance of an adequate sample size and quantify the uncertainties arising from the limited number of observations.https://ojs.cvut.cz/ojs/index.php/APP/article/view/8370bayesian updatingbootstrappingburn-inconcrete compressive strengthmarkov chain monte carlomcmcmetropolis algorithmroding bridgestructural reassessment |
| spellingShingle | Matthias Haslbeck Robert Kroyer Andreas Taras Thomas Braml Uncertainty assessment for the Bayesian updating process of concrete strength properties Acta Polytechnica CTU Proceedings bayesian updating bootstrapping burn-in concrete compressive strength markov chain monte carlo mcmc metropolis algorithm roding bridge structural reassessment |
| title | Uncertainty assessment for the Bayesian updating process of concrete strength properties |
| title_full | Uncertainty assessment for the Bayesian updating process of concrete strength properties |
| title_fullStr | Uncertainty assessment for the Bayesian updating process of concrete strength properties |
| title_full_unstemmed | Uncertainty assessment for the Bayesian updating process of concrete strength properties |
| title_short | Uncertainty assessment for the Bayesian updating process of concrete strength properties |
| title_sort | uncertainty assessment for the bayesian updating process of concrete strength properties |
| topic | bayesian updating bootstrapping burn-in concrete compressive strength markov chain monte carlo mcmc metropolis algorithm roding bridge structural reassessment |
| url | https://ojs.cvut.cz/ojs/index.php/APP/article/view/8370 |
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