Analysis of arch bridge condition data to identify network-wide controls and trends

Kristopher Campbell; Myra Lydon; Nicola-Ann Stevens; Su Taylor

doi:10.3390/infrastructures9040070

Analysis of arch bridge condition data to identify network-wide controls and trends

Kristopher Campbell^*
, Myra Lydon
, Nicola-Ann Stevens
, Su Taylor^*

^*Corresponding author for this work

School of Natural and Built Environment

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

121 Downloads (Pure)

Abstract

This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.

Original language	English
Article number	70
Number of pages	14
Journal	Infrastructures
Volume	9
Issue number	4
DOIs	https://doi.org/10.3390/infrastructures9040070
Publication status	Published - 04 Apr 2024

Keywords

Computer Science Applications
Geotechnical Engineering and Engineering Geology
General Materials Science
Building and Construction
Civil and Structural Engineering

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10.3390/infrastructures9040070Licence: CC BY

Analysis of arch bridge condition data to identify network-wide controls and trends
Copyright 2024 The Authors. This is an open access article published under a Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
Final published version, 11.2 MBLicence: CC BY

Enhancing the resilience of the bridge network by identifying key performance indicators through survival analysis and evaluation of maintenance prioritisation and budgeting methods
Stevens, N.-A. (Author), Lydon, M. (Supervisor), Marshall, A. (Supervisor) & Taylor, S. (Supervisor), Dec 2024
Student thesis: Doctoral Thesis › Doctor of Philosophy

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Managing scour risk for effective bridge management decisions across Northern Ireland
Campbell, K. (Author), Taylor, S. (Supervisor), Lydon, M. (Supervisor), Amato, G. (Supervisor) & O'Connor, A. (Supervisor), Jul 2026
Student thesis: Doctoral Thesis › Doctor of Philosophy (Thesis with Publications)

File

Cite this

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title = "Analysis of arch bridge condition data to identify network-wide controls and trends",

abstract = "This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56\% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge{\textquoteright}s lifecycle. ",

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doi = "10.3390/infrastructures9040070",

language = "English",

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journal = "Infrastructures",

issn = "2412-3811",

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TY - JOUR

T1 - Analysis of arch bridge condition data to identify network-wide controls and trends

AU - Campbell, Kristopher

AU - Lydon, Myra

AU - Stevens, Nicola-Ann

AU - Taylor, Su

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N2 - This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.

AB - This paper outlines an initial analysis of 20 years of data held on an electronic bridge management database for approximately 3500 arch bridges across Northern Ireland (NI) by the Department for Infrastructure. Arch bridges represent the largest group of bridge types, making up nearly 56% of the total bridge stock in NI. This initial analysis aims to identify trends that might help inform maintenance decisions in the future. Consideration of the Bridge Condition Indicator (BCI) average value for the overall arch bridge stock indicates the potential for regional variations in the overall condition and the potential for human bias in inspections. The paper presents the most prevalent structural elements and associated defects recorded in the inspections of arch bridges. This indicated a link to scour and undermining for the worst-conditioned arch bridges. An Analysis of Variance (ANOVA) analysis identified function, number of spans, and deck width as significant factors during the various deterioration stages in a bridge’s lifecycle.

KW - Computer Science Applications

KW - Geotechnical Engineering and Engineering Geology

KW - General Materials Science

KW - Building and Construction

KW - Civil and Structural Engineering

U2 - 10.3390/infrastructures9040070

DO - 10.3390/infrastructures9040070

M3 - Article

SN - 2412-3811

VL - 9

JO - Infrastructures

JF - Infrastructures

IS - 4

M1 - 70

ER -

Analysis of arch bridge condition data to identify network-wide controls and trends

Abstract

Keywords

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Student theses

Enhancing the resilience of the bridge network by identifying key performance indicators through survival analysis and evaluation of maintenance prioritisation and budgeting methods

Managing scour risk for effective bridge management decisions across Northern Ireland

Cite this