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Stochastic Multiphasic Multivariate State-Based Degradation and Maintenance Meta-Models for RC Structures Subject to Chloride Ingress

Auteur(s): (Ecole Centrale Nantes, CNRS, GeM, UMR 6183, IUML FR 3473, Nantes Université, F-44300 Nantes, France)
(LARIS EA 7315, Angers University, 49100 Angers, France)
ORCID (Ecole Centrale Nantes, CNRS, GeM, UMR 6183, IUML FR 3473, Nantes Université, F-44300 Nantes, France)
ORCID (Laboratory of Engineering Sciences for the Environment (LaSIE—UMR CNRS 7356), La Rochelle University, 17000 La Rochelle, France)
Médium: article de revue
Langue(s): anglais
Publié dans: Infrastructures, , n. 2, v. 8
Page(s): 36
DOI: 10.3390/infrastructures8020036
Abstrait:

The objective of this paper is to propose tools for the lifecycle management of infrastructure by showing the slow degradation processes for which inspection data are accessible, especially the data obtained from non-destructive testing (NDT) and structural health monitoring (SHM). One major characteristic of these degradation processes is their multiphasic nature; consequently, they can be discretised into different phases with specific physical kinematics where specific maintenance actions and measurement techniques can be performed. Within this framework, we propose implementing a degradation meta-modelling approach fed with measurements (NDT, SHM). This approach is based on state-dependent stochastic processes for modelling the degradation and maintenance of reinforced concrete structures that are subjected to chloride-induced deterioration. The benefit of using multiphasic degradation meta-models in the lifecycle management of infrastructure is illustrated through numerical examples that include single and multi-action management policies.

Copyright: © 2023 the Authors. Licensee MDPI, Basel, Switzerland.
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
    10722735
  • Publié(e) le:
    22.04.2023
  • Modifié(e) le:
    10.05.2023
 
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