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Numerical Investigation on the Performance of Exterior Beam–Column Joints Reinforced with Shape Memory Alloys

Autor(en): ORCID
ORCID
ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 7, v. 13
Seite(n): 1801
DOI: 10.3390/buildings13071801
Abstrakt:

Upgraded design standards coupled with the damage caused by natural disasters have led to the development of smart materials with the potential to modernize current construction practices. This investigation proposes a nonlinear finite element (FE) model for evaluating the performance of beam–column joints (RC-BCJ) reinforced with shape memory alloys (SMA) and steel rebars. The model was validated based on accredited experimental data, followed by parametric analysis in ABAQUS to optimize the use of SMA bars for enhancing the seismic resistance of RC-BCJ without compromising their energy dissipation capacity. Parameters investigated include the (a) SMA–steel reinforcement ratio, (b) lengths of SMA bars, (c) elastic modulus of SMA, (d) compressive strength of concrete, and (e) axial load applied on the column. The finite element simulation results indicated that the model was capable of predicting the optimum length of SMA bars sufficient for relocating the plastic hinge away from the face of the column along the beam. Further, simulation results proved that the use of SMA bars in conjunction with steel reinforcement could be considered as an effective tool for enhancing the seismic performance of RC-BCJ joints. Among the parameters investigated, high-strength concrete was the most effective in improving joint resistance.

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
    10737164
  • Veröffentlicht am:
    03.09.2023
  • Geändert am:
    14.09.2023
 
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