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A Monte Carlo-Based Approach to Assess the Reinforcement Depassivation Probability of RC Structures: Simulation and Analysis

Autor(en): ORCID


ORCID
ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 4, v. 13
Seite(n): 993
DOI: 10.3390/buildings13040993
Abstrakt:

In this work, an approach is presented to assess the reinforcement depassivation probability of reinforced concrete structures under corrosion induced by carbonation or chloride diffusion. The model consists of coupling mathematical formulations of CO2 and Cl− diffusion with Monte Carlo simulation (MCS). Random events were generated using MCS to create several design life and environmental scenarios. A case study was performed by simulating five Brazilian environmental conditions and distinct mixes of concrete. The effect of input parameters on the reinforcement concrete depassivation probability was evaluated. The results point out that the depassivation probability due to carbonation is more significant in urban centers, and the compressive strength of concrete has the main influence on the depassivation probability. Results also showed that the depassivation probability due to chloride ingress is influenced by, in order of importance, the chloride content on the surface (61.4%), concrete cover (20.3%), compressive strength (7.1%), relative humidity (6.1%), and temperature (5.1%). In addition, an increase in the compressive strength of concrete, from 30 to 50 MPa, can reduce depassivation probability by up to 70%, resulting in a concrete structure that attends the durability limit state. Thus, by incorporating probabilistic approaches, this model can be a valuable tool in the civil construction industry for studying the improvement of durability, reliability, and safety of reinforced concrete structures.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10728029
  • Veröffentlicht am:
    30.05.2023
  • Geändert am:
    01.06.2023
 
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