• Title of article

    Analytical prediction of the seismic behaviour of superelastic shape memory alloy reinforced concrete elements

  • Author/Authors

    Alam، نويسنده , , M.S. and Youssef، نويسنده , , M.A. and Nehdi، نويسنده , , M.، نويسنده ,

  • Issue Information
    روزنامه با شماره پیاپی سال 2008
  • Pages
    13
  • From page
    3399
  • To page
    3411
  • Abstract
    Superelastic shape memory alloys (SMAs) are unique materials that have the ability to undergo large deformations, but can return to their undeformed shape by the removal of stress. If such materials can be used as reinforcement in plastic hinge regions of beam–column elements, they will not only experience large inelastic deformations during strong earthquakes, but can potentially recover their original shape. This behaviour will allow mitigating the problem of permanent deformation. Hence, this study aims at establishing guidelines for predicting the seismic behaviour of concrete beam–column elements reinforced with superelastic SMAs. The paper identifies the disparities in moment–curvature relationship between SMA and steel reinforced sections. Then it examines the applicability of existing methods developed for steel reinforced concrete (RC) members to predict the length of the plastic hinge, crack width, crack spacing, and bond-slip relationship for superelastic SMA RC elements. Existing superelastic SMA models are discussed and the application of one of the models in a finite element (FE) program is presented. This FE program is used to simulate the behaviour of an SMA RC column and a beam–column joint. The predicted load–displacement, moment–rotation relationships and energy dissipation capacities have been found to be in good agreement with experimental results.
  • Keywords
    Shape memory alloy , superelasticity , Plastic hinge length , Crack , Load–displacement , Moment–rotation , Beam–column joint
  • Journal title
    Engineering Structures
  • Serial Year
    2008
  • Journal title
    Engineering Structures
  • Record number

    1643514