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Recent progress and future outlook of digital twins in structural health monitoring of civil infrastructure

Auteur(s):
ORCID
Médium: article de revue
Langue(s): anglais
Publié dans: Smart Materials and Structures, , n. 3, v. 33
Page(s): 033001
DOI: 10.1088/1361-665x/ad2bd7
Abstrait:

Digital twins (DTs) have witnessed a paramount increase in applications in multidisciplinary engineering systems. With advancements in structural health monitoring (SHM) methods and implementations, DT-based maintenance and operation stages have been implemented significantly during the life cycle of civil infrastructure. Recent literature has started laying the building blocks for incorporating the concept of DTs with SHM of large-scale civil infrastructure. This paper undertakes a systematic literature review of studies on DT-related applications for SHM of civil structures. It classifies the articles based on thematic case studies: transportation infrastructure (i.e. bridges, tunnels, roads, and pavements), buildings, off-shore marine infrastructure and wind turbines, and other civil engineering systems. The proposed review is further uniquely sub-classified using diverse modeling approaches such as building information modeling, finite element modeling, 3D representation, and surrogate and hybrid modeling used in DT implementations. This paper is solely focused on applications relating DTs to SHM practices for various civil engineering infrastructures, hence highlighting ist novelty over previous reviews. Gaps and limitations emerging from the systematic review are presented, followed by articulating future research directions and key conclusions.

Copyright: © 2024 Micheal Sakr, Ayan Sadhu
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
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  • Reference-ID
    10769273
  • Publié(e) le:
    29.04.2024
  • Modifié(e) le:
    05.06.2024
 
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