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Abstract:
Superelastic shape memory alloys (SMAs) have inherent properties of complete recovery of large deformation and satisfactory energy dissipation under cyclic loadings. Such properties have attracted wide attention within the earthquake engineering community, especially for the perspective of developing self-centering (SC) structures. SMA braced frames (SMABFs) have emerged in recent years as one of promising SC frames. This paper presents a seismic design methodology for SMABFs using the hysteretic energy spectrum. The underlying principle for the proposed design methodology is that both the total hysteretic energy and accumulated ductility demands in earthquake resistant structures are correlated with the maximum endured deformation. With the quantitative relationship, the seismic performance target, such as the maximum interstory drift ratio, can be readily achieved. The spectra of hysteretic energy and accumulated ductility demands are first constructed in this study for the single-degree-of-freedom (SDOF) systems which represent the global behavior of SMABFs. The SDOF system based results were then utilized for the development of an iterative design procedure for multistory SMABFs. Both 3- and 6-story SMABFs are designed for representative low-to-medium rise building structures and subjected to a suite of earthquake ground motions scaled to the design basis earthquake (DBE) and maximum considered earthquake (MCE) seismic hazard levels. Computational simulation results show that the designed SMABFs satisfy the performance target very well. The proposed methodology is demonstrated to be effective and efficient for seismic design of SMABFs, but could also shed light on other SC structures. (C) 2019 American Society of Civil Engineers.
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JOURNAL OF STRUCTURAL ENGINEERING
ISSN: 0733-9445
Year: 2020
Issue: 2
Volume: 146
4 . 1 0 0
JCR@2022
ESI Discipline: ENGINEERING;
ESI HC Threshold:115
Cited Count:
WoS CC Cited Count: 42
SCOPUS Cited Count: 47
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 5
Affiliated Colleges: