Sensor-Based Structural Assessment of Aging Bridges


Transport infrastructure managers need to ensure longevity of their networks to meet pressing sustainability demands. Extending the operational life of complex structural systems, such as aging bridges, requires a comprehensive life-expectancy assessment. Given that these structures are suffering from local failures that may not necessarily alter their global response, engineers need to increase their confidence in detecting and characterizing such damage, while assessing deterioration rates in localized regions. This chapter presents data analysis results from the structural health monitoring of three aging bridges: two masonry arch rail bridges, and a half-joint concrete motorway bridge. The aim, in all cases, is to improve deterioration assessment through enhanced sensing of the distributed response across the structures. A core sensing technology used in the three schemes is the development of fiber Bragg grating (FBG) networks, allowing the study of small dynamic strain variations at both the local and global response levels. New ways of installing FBGs are explored for multi-aspect condition monitoring, while their sensitivity in damage detection is enhanced with data analytics and acoustic emission (AE) sensors. The chapter discusses that complementing information from dynamic strain and AE-sensing networks may enable a finer deterioration monitoring of aging structures driven by data.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > School of Infrastructure and Sustainable Engineering > Civil Engineering
College of Engineering & Physical Sciences
Additional Information: This is an Accepted Manuscript of a book chapter published by CRC Press in Data Driven Methods for Civil Structural Health Monitoring and Resilience on 26 October 2023, available online: It is deposited under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License (, which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited, and is not altered, transformed, or built upon in any way.
Uncontrolled Keywords: General Engineering
ISBN: 9781032308371, 9781000965551, 9781003306924
Last Modified: 12 Jul 2024 17:26
Date Deposited: 09 Feb 2024 12:58
Full Text Link:
Related URLs: https://www.tay ... -matthew-dejong (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Chapter
Published Date: 2023-10-26
Authors: Alexakis, Haris (ORCID Profile 0000-0002-6588-2070)
Cocking, Sam
Tziavos, Nikolaos I. (ORCID Profile 0000-0002-3692-9626)
Din-Houn Lau, F.
Schooling, Jennifer
DeJong, Matthew



Version: Accepted Version

Access Restriction: Restricted to Repository staff only until 26 October 2024.

License: Creative Commons Attribution Non-commercial No Derivatives

Export / Share Citation


Additional statistics for this record