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Tunnel lining detection and retrofitting.

Authors :
Jiang, Yandan
Wang, Lai
Zhang, Bo
Dai, Xiaowei
Ye, Jun
Sun, Bochao
Liu, Nianwu
Wang, Zhen
Zhao, Yang
Source :
Automation in Construction. Aug2023, Vol. 152, pN.PAG-N.PAG. 1p.
Publication Year :
2023

Abstract

The underground tunnel structure is important and common in transport infrastructures. With the increasing service time, it is crucial to detect the deteriorations in the ageing tunnel linings and make informed retrofitting decisions to ensure their structural safety and extend their service life cycle. This emphasizes the importance of understanding the framework of tunnel lining detection, evaluation, and retrofitting. However, there is no up-to-date review available that covers the entire workflow of tunnel lining detection and retrofitting. This paper provides a comprehensive review of non-destructive testing (NDT) methods, health evaluation methods, and retrofitting methods for tunnel linings. The achievements, challenges, and development trends of these methods are illustrated. Specifically, NDT methods for three representative tunnel lining defects, including cracks, leakage, and voids, are introduced and analyzed to show the corresponding advantages and disadvantages. Based on the data obtained by the defect detection methods, the procedures for lining health status evaluation are also summarized to provide a systematic and quantitative evaluation of tunnel linings. Finally, the retrofitting methods and techniques that are suitable for lining structures are reviewed. This paper provides an insight into the development of structural health monitoring (SHM) and the maintenance of tunnel linings, offering a systematic guide for understanding the framework of tunnel lining detection and retrofitting. [Display omitted] • Review of the detection methods of tunnel lining defects and their applications • Review of the existing evaluation methods of tunnel lining conditions • Review of the available tunnel lining retrofitting methods • Gaps and outlook for tunnel lining detection and retrofitting research [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09265805
Volume :
152
Database :
Academic Search Index
Journal :
Automation in Construction
Publication Type :
Academic Journal
Accession number :
164285550
Full Text :
https://doi.org/10.1016/j.autcon.2023.104881