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Empirical Equations for Modelling Yarn–Mortar Debonding in TRM-Strengthened Masonry Walls Subjected to Out-of-Plane Loading

Autor(en): ORCID
ORCID


Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 1, v. 14
Seite(n): 32
DOI: 10.3390/buildings14010032
Abstrakt:

The effectiveness of textile-reinforced mortar (TRM) strengthening of masonry walls largely depends on the bond between the constituent materials. Finite element analysis (FEA) can provide valuable insights on the effect of the parameters affecting the bond; however, detailed FEA is computationally intensive. To alleviate this, we develop novel empirical equations to estimate effective textile fibre properties, thus implicitly accounting for yarn and mortar debonding. As a result, 3D finite element simulations of strengthened wall specimens are simplified and accelerated. The proposed scheme is calibrated using load–displacement paths derived from experimental data, and the simulated failure modes are compared against the experimental ones demonstrating perfect agreement. A parametric analysis is conducted, exploring the impact of the mechanical ratio of TRM reinforcement and the axial wall load on the effectiveness of TRM strengthening. We demonstrate that low values of mechanical reinforcement, corresponding to natural fibres, give rise to an 8-fold increase in the capacity of unreinforced walls. The findings draw conclusions about the efficacy of TRM strengthening in masonry structures, and provide valuable insights for optimising TRM reinforcement, considering different fibre materials and axial loads in masonry 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
    10754006
  • Veröffentlicht am:
    14.01.2024
  • Geändert am:
    07.02.2024
 
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