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Shape Memory Alloy‐Based Seismic Retrofit of an existing URM Building

Author(s): (Institute of Metal Structures, Department of Civil Engineering Aristotle University of Thessaloniki Thessaloniki Greece)
(Institute of Metal Structures, Department of Civil Engineering Aristotle University of Thessaloniki Thessaloniki Greece)
Medium: journal article
Language(s): English
Published in: ce/papers, , n. 3-4, v. 6
Page(s): 417-422
DOI: 10.1002/cepa.2699
Abstract:

Masonry buildings constitute a considerable part of the existing building stock and are often related to significant architectural and cultural value. Empirical construction, accumulated damage, material heterogeneity and anisotropic behavior deteriorate their structural and seismic capacity, increasing thus the risk of undergoing severe damage and even collapse. To enhance these buildings' performance, various retrofit schemes have been developed and have been included in current codes and standards, mostly utilizing conventional materials and improvement of their intervention techniques. Recently, research efforts are oriented to the application of emerging metal materials with advanced properties endowed with re‐centering abilities that conventional materials lack, aiming to achieve vibration control and mitigate potential structural damage.

This work investigates the use of shape memory alloys (SMAs) for the seismic protection of masonry buildings focusing on the exploitation of their superelastic effect, namely the ability to revert to their original shape after being subjected to large deformations. The research adopts a case study approach, developing an SMA based retrofit scheme to be applied to an existing listed unreinforced masonry building in Thessaloniki. For the purposes of the study, finite element modeling is performed, while response spectrum analysis is carried out to assess the effectiveness of the introduced retrofit strategy.

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.1002/cepa.2699.
  • About this
    data sheet
  • Reference-ID
    10767363
  • Published on:
    17/04/2024
  • Last updated on:
    17/04/2024
 
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