Bayesian assessment of an existing bridge - a case study

This article presents a case study involving the assessment of an existing bridge, starting with simple methods and ending with a probabilistic analysis, the latter emphasising Bayesian methods. When assessing an existing bridge, it is common practice to collect information from the bridge in the fo...

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Main Authors: Jacinto, Luciano, Neves, Luís Canhoto, Santos, Luís Oliveira
Format: Article
Language:English
Published: Taylor & Francis 2015
Subjects:
Online Access:https://eprints.nottingham.ac.uk/34492/
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author Jacinto, Luciano
Neves, Luís Canhoto
Santos, Luís Oliveira
author_facet Jacinto, Luciano
Neves, Luís Canhoto
Santos, Luís Oliveira
author_sort Jacinto, Luciano
building Nottingham Research Data Repository
collection Online Access
description This article presents a case study involving the assessment of an existing bridge, starting with simple methods and ending with a probabilistic analysis, the latter emphasising Bayesian methods. When assessing an existing bridge, it is common practice to collect information from the bridge in the form of samples. These samples are in general of small size, raising the question of how the corresponding statistical uncertainty can be taken into account on reliability estimates. The case study illustrates how Bayesian methods are especially suitable to deal with that source of uncertainty. Another strong point of the Bayesian methods is their ability to combine the information contained in the samples collected from the bridge with prior information, if any. This aspect will also be illustrated through the case study.
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spelling nottingham-344922017-10-13T21:21:32Z https://eprints.nottingham.ac.uk/34492/ Bayesian assessment of an existing bridge - a case study Jacinto, Luciano Neves, Luís Canhoto Santos, Luís Oliveira This article presents a case study involving the assessment of an existing bridge, starting with simple methods and ending with a probabilistic analysis, the latter emphasising Bayesian methods. When assessing an existing bridge, it is common practice to collect information from the bridge in the form of samples. These samples are in general of small size, raising the question of how the corresponding statistical uncertainty can be taken into account on reliability estimates. The case study illustrates how Bayesian methods are especially suitable to deal with that source of uncertainty. Another strong point of the Bayesian methods is their ability to combine the information contained in the samples collected from the bridge with prior information, if any. This aspect will also be illustrated through the case study. Taylor & Francis 2015-01-06 Article PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/34492/1/Bayesian%20assessment%20of%20an%20existing%20bridge%20A%20case%20study.pdf Jacinto, Luciano, Neves, Luís Canhoto and Santos, Luís Oliveira (2015) Bayesian assessment of an existing bridge - a case study. Structure and Infrastructure Engineering, 12 (1). pp. 61-77. ISSN 1744-8980 Existing bridges; probabilistic assessment; Bayesian updating; statistical uncertainty; predictive model http://dx.doi.org/10.1080/15732479.2014.995105 doi: 10.1080/15732479.2014.995105 doi: 10.1080/15732479.2014.995105
spellingShingle Existing bridges; probabilistic assessment; Bayesian updating; statistical uncertainty; predictive model
Jacinto, Luciano
Neves, Luís Canhoto
Santos, Luís Oliveira
Bayesian assessment of an existing bridge - a case study
title Bayesian assessment of an existing bridge - a case study
title_full Bayesian assessment of an existing bridge - a case study
title_fullStr Bayesian assessment of an existing bridge - a case study
title_full_unstemmed Bayesian assessment of an existing bridge - a case study
title_short Bayesian assessment of an existing bridge - a case study
title_sort bayesian assessment of an existing bridge - a case study
topic Existing bridges; probabilistic assessment; Bayesian updating; statistical uncertainty; predictive model
url https://eprints.nottingham.ac.uk/34492/
https://eprints.nottingham.ac.uk/34492/
https://eprints.nottingham.ac.uk/34492/