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An Experimental Approach to Assess the Sensitivity of a Smart Concrete

Autor(en): ORCID



Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 8, v. 13
Seite(n): 2034
DOI: 10.3390/buildings13082034
Abstrakt:

Structural health monitoring of concrete infrastructure is a critical concern for timely repair and maintenance. This study provides an innovative approach utilizing smart concrete integrated with multi-walled carbon nanotubes (MWCNTs) to enhance electrical conductivity. The smart concrete’s self-sensing capability is assessed through fractional change in electrical resistance (FCR) measured using a four-probe technique. Four-point bending and compressive tests explore the material’s response to cyclic and monotonic loads. Additionally, the impact of saturation levels on self-sensing sensitivity is investigated through compressive tests on varying saturation degrees. Remarkably, a substantial correlation between crack mouth opening displacement (CMOD) and FCR is observed during cyclic bending tests, where FCR increases significantly (from 0.019% to 154%) as CMOD rises from 0.004 mm to 0.55 mm. Digital image correlation (DIC) further validates CMOD measurements and their correlation with FCR. Moreover, this study reveals that amplitude of loading and degree of saturation have a significant effect on the self-sensing of the smart concrete. In saturated conditions, the self-sensing response of the material is insensitive to the mechanical strain, while with reduction in the saturation degree, a quasi-linear response is observed. To assess the sensitivity of the smart concrete, stress and strain sensitivities were evaluated, revealing a noteworthy enhancement of approximately 33% and 50% in stress and strain sensitivity, respectively, as saturation levels decreased. The self-sensing response of the material is very sensitive to the mechanical strain during monotonic loading and damage. These findings indicate the potential of smart concrete as a promising tool for comprehensive, real-time structural health monitoring for infrastructure during its entire life.

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
    10737214
  • Veröffentlicht am:
    02.09.2023
  • Geändert am:
    14.09.2023
 
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