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Visual inspection and bridge management

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Author(s)
Quirk, Lucy 
Matos, Jose 
Murphy, Jimmy 
Pakrashi, Vikram 
Uri
http://hdl.handle.net/10197/10351
Date Issued
04 March 2018
Date Available
08T12:54:20Z May 2019
Abstract
This paper estimates visual inspection quantitatively prior to its implementation in a Bridge Management System using a Value of Information (VoI) approach employing a Bayesian pre-posterior analysis. Information from a significant number of real bridges from Ireland and Portugal are considered in this regard following existing commercial practices. The variation of different parameters on the estimated VoI is investigated including the assumed probabilistic models of the prior bridge state, the likelihood of inspector assigned condition ratings and the economic setting surrounding the cost matrix for maintenance decision alternatives. The values of no information, perfect information and imperfect information are presented and the change in the optimal strategy based on such information is assessed. The effect of human imperfections in assessment and difference in condition rating scale are also estimated. The studies and findings of this paper are expected to allow a better insight for practising engineers and researchers working in bridge management.
Other Sponsorship
COST (European Cooperation in Science and Technology).
Type of Material
Journal Article
Publisher
Taylor & Francis
Journal
Structure and Infrastructure Engineering
Volume
14
Issue
3
Start Page
320
End Page
332
Copyright (Published Version)
2017 Taylor & Francis
Keywords
  • Bridge maintenance

  • Visual inspection

  • Condition rating

  • Value engineering

  • Cost estimates

  • Decision-making

  • Bayesian Networks

DOI
10.1080/15732479.2017.1352000
Language
English
Status of Item
Peer reviewed
ISSN
1573-2479
This item is made available under a Creative Commons License
https://creativecommons.org/licenses/by-nc-nd/3.0/ie/
Owning collection
Mechanical & Materials Engineering Research Collection
Scopus© citations
35
Acquisition Date
Feb 6, 2023
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