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Uncertainty in condition prediction of bridges based on assessment method – case study in Estonia

 Uncertainty in condition prediction of bridges based on assessment method – case study in Estonia
Autor(en): , , ORCID
Beitrag für IABSE Symposium: Towards a Resilient Built Environment Risk and Asset Management, Guimarães, Portugal, 27-29 March 2019, veröffentlicht in , S. 1758-1765
DOI: 10.2749/guimaraes.2019.1758
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In this paper the uncertainty in condition assessment based on most common assessment methods, visual inspection and non-destructive testing, is investigated. For decision-making the averaged or es...
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Bibliografische Angaben

Autor(en): (Tallinn University of Technology, Tallinn, Estonia)
(Tallinn University of Technology, Tallinn, Estonia)
ORCID (University of Minho, Guimarães, Portugal)
Medium: Tagungsbeitrag
Sprache(n): Englisch
Tagung: IABSE Symposium: Towards a Resilient Built Environment Risk and Asset Management, Guimarães, Portugal, 27-29 March 2019
Veröffentlicht in:
Seite(n): 1758-1765 Anzahl der Seiten (im PDF): 8
Seite(n): 1758-1765
Anzahl der Seiten (im PDF): 8
DOI: 10.2749/guimaraes.2019.1758
Abstrakt:

In this paper the uncertainty in condition assessment based on most common assessment methods, visual inspection and non-destructive testing, is investigated. For decision-making the averaged or estimated value is suitable, but if the basis of a decision is only a subjective visual inspection, then it could lead to a wrong decision. The second most traditional assessment method is non-destructive testing (NDT), which can give reliable results, but the interpretation of measurement is needed. To investigate the errors in both evaluations, benchmarking tests were carried out in Estonia within two groups, a group of experienced inspectors and a group of unexperienced students, to show how the importance of experience affects results. To present the influence of assessment uncertainty to condition prediction curves based on continuous-time Markov model are calculated and for updating, Bayesian inference procedure is used.

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