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...

Full description

Saved in:
Bibliographic Details
Main Authors: Matthias Haslbeck, Robert Kroyer, Andreas Taras, Thomas Braml
Format: Article
Language:English
Published: Czech Technical University in Prague 2022-08-01
Series:Acta Polytechnica CTU Proceedings
Subjects:
Online Access:https://ojs.cvut.cz/ojs/index.php/APP/article/view/8370
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1850064270154268672
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
work_keys_str_mv AT matthiashaslbeck uncertaintyassessmentforthebayesianupdatingprocessofconcretestrengthproperties
AT robertkroyer uncertaintyassessmentforthebayesianupdatingprocessofconcretestrengthproperties
AT andreastaras uncertaintyassessmentforthebayesianupdatingprocessofconcretestrengthproperties
AT thomasbraml uncertaintyassessmentforthebayesianupdatingprocessofconcretestrengthproperties