Synthesized Evaluation of Reinforced Concrete Bridge Defects, Their Non-Destructive Inspection and Analysis Methods: A Systematic Review and Bibliometric Analysis of the Past Three Decades

Abstract

Defects are essential indicators to gauge the structural integrity and safety of reinforced concrete bridges. Non-destructive inspection has been pervasively explored over the last three decades to localize and characterize surface and subsurface anomalies in reinforced concrete bridges. In addition, different fuzzy set theory-based, computer vision and artificial intelligence algorithms were leveraged to analyze the data garnered from non-destructive evaluation techniques. In light of the foregoing, this research paper presents a mixed review method that encompasses both bibliometric and systematic analyses of the state-of-the-art work pertinent to the assessment of reinforced concrete bridge defects using non-destructive techniques (CBD_NDT). In this context, this study reviews the literature of journal articles and book chapters indexed in Scopus and Web of Science databases from 1991 to the end of September 2022. To this end, 505 core peer-reviewed journal articles and book chapters are compiled for evaluation after conducting forward and backward snowballing alongside removing irrelevant papers. This research study then exploits both VOSVIEWER and Bibiometrix R Package for the purpose of network visualization and scientometric mapping of the appended research studies. Thereafter, this paper carries out a multifaceted systematic review analysis of the identified literature covering tackled bridge defects, used non-destructive techniques, data processing methods, public datasets, key findings and future research directions. The present study is expected to assist practitioners and policymakers to conceive and synthesize existing research and development bodies, and future trends in the domain of the assessment of bridge defects using non-destructive techniques. It can also aid in raising awareness of the importance of defect management in bridge maintenance systems.

Autonomous Identification of Bridge Concrete Cracks Using Unmanned Aircraft Images and Improved Lightweight Deep Convolutional Networks

“…Traditional nondestructive testing instruments and manual testing methods have certain advantages in detecting internal structural defects of bridges [4][5][6][7]. However, there are still certain shortcomings in realizing large-scale defect detection of bridges, which are limited by inspection efciency and accuracy [8].…”

Harnessing the Power of ChatGPT for Automating Systematic Review Process: Methodology, Case Study, Limitations, and Future Directions

“…SRs offer several advantages, such as providing a reliable and comprehensive assessment of evidence, guiding evidence-based practice and policymaking, identifying research gaps, and enhancing statistical power through meta-analysis [4,5]. It is worth mentioning that SR articles are a valuable tool for synthesizing and analyzing research evidence in many fields of research, particularly in fields where research evidence is constantly evolving, such as in healthcare [6][7][8][9], project management [10][11][12][13], construction management [14][15][16][17][18][19], and aviation routing management [20,21]. To ensure that SRs are reported accurately and comprehensively, PRISMA (Preferred Reporting Items for SRs and Meta-Analyses) is widely used.…”

Level 3 Assessment of Highway Girder Deck Bridges according to the Italian Guidelines: Influence of Transverse Load Distribution

“…As known, a detailed assessment needs an in-depth knowledge of the structure derived from an in situ experimental testing campaign [7]. It is worth noting that in the case of high and medium-high CoA a permanent structural health monitoring system must be installed on the bridge [8,9]. Level 5 is devoted to the evaluations of the bridge at the road network level.…”