Structural assessment of bridges using monitoring data
type: CreativeWork
description: Despite decades of research, there has been relatively little industry uptake of structural health monitoring (SHM) technologies and model updating techniques, i.e., the integration of structural monitoring data with structural analysis modelling, in bridge operation and maintenance (O\&M) activities. Many bridge practitioners question whether these technologies and techniques can provide valuable and reliable information on bridge safety and performance. In the first part of this PhD thesis, a series of industry interviews are used to investigate the reasons behind this limited industry adoption and the disconnects between research and practice regarding bridge monitoring and model updating. It has been found that while most studies in the bridge SHM community have been focused on damage detection, many bridge practitioners are ultimately more interested in bridge capacity assessment, and in particular, the ``margin of capacity'' of their bridge assets (i.e., how much additional live load can be safely placed on a bridge). In addition, bridge assessment remains a key asset management challenge in that there has been a consistent mismatch between the calculated load rating and the actual capacity of bridges. These findings form the basis of the second part of this PhD thesis, which investigates how strain monitoring data may be utilised to improve bridge assessment by (i) better understanding and quantifying commonly made assumptions about structural behaviour to enable more realistic bridge modelling and analysis, and (ii) evaluating in-service structural utilisation to better understand the ``margin of capacity'', which is defined in this PhD study as how much additional live load can be safely placed on a bridge without violating the design performance criteria. First, four common assumptions about structural behaviour in bridge assessment are examined. These are the amount of prestress loss (for prestressed concrete bridges), load distribution characteristics, s…
abstract: Despite decades of research, there has been relatively little industry uptake of structural health monitoring (SHM) technologies and model updating techniques, i.e., the integration of structural monitoring data with structural analysis modelling, in bridge operation and maintenance (O\&M) activities. Many bridge practitioners question whether these technologies and techniques can provide valuable and reliable information on bridge safety and performance. In the first part of this PhD thesis, a series of industry interviews are used to investigate the reasons behind this limited industry adoption and the disconnects between research and practice regarding bridge monitoring and model updating. It has been found that while most studies in the bridge SHM community have been focused on damage detection, many bridge practitioners are ultimately more interested in bridge capacity assessment, and in particular, the ``margin of capacity'' of their bridge assets (i.e., how much additional live load can be safely placed on a bridge). In addition, bridge assessment remains a key asset management challenge in that there has been a consistent mismatch between the calculated load rating and the actual capacity of bridges. These findings form the basis of the second part of this PhD thesis, which investigates how strain monitoring data may be utilised to improve bridge assessment by (i) better understanding and quantifying commonly made assumptions about structural behaviour to enable more realistic bridge modelling and analysis, and (ii) evaluating in-service structural utilisation to better understand the ``margin of capacity'', which is defined in this PhD study as how much additional live load can be safely placed on a bridge without violating the design performance criteria. First, four common assumptions about structural behaviour in bridge assessment are examined. These are the amount of prestress loss (for prestressed concrete bridges), load distribution characteristics, s…
author: Ye, Cong
language: eng
keywords: civil engineering, structural engineering, bridge engineering, structural health monitoring, fibre optic sensing, model updating, bridge assessment, structural behaviour, structural utilisation, uncertainty analysis, prestressed concrete bridge, railway bridge, infrastructure management, industry interview
license: https://www.rioxx.net/licenses/all-rights-reserved/
date published: 2022-02-05
date modified: 2026-07-22T22:24:24Z
provider: Cambridge University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Cambridge

PropertyValue
property ID: DOI
value: 10.17863/CAM.89342