Parametric computational study on butterfly-shaped hysteretic dampers

Alireza FARZAMPOUR, Matthew Roy EATHERTON

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PDF(2297 KB)
Front. Struct. Civ. Eng. ›› 2019, Vol. 13 ›› Issue (5) : 1214-1226. DOI: 10.1007/s11709-019-0550-6
RESEARCH ARTICLE
RESEARCH ARTICLE

Parametric computational study on butterfly-shaped hysteretic dampers

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Abstract

A parametric computational study is conducted to investigate the shear yielding, flexural yielding, and lateral torsional buckling limit states for butterfly-shaped links. After validating the accuracy of the finite element modeling approach against previous experiments, 112 computational models with different geometrical properties were constructed and analyzed including consideration of initial imperfections. The resulting yielding moment, corresponding critical shear force, the accumulation of plastic strains through the length of links as well as the amount of energy dissipated are investigated. ‚€ƒThe results indicate that as the shape of the butterfly-shaped links become too straight or conversely too narrow in the middle, peak accumulated plastic strains increase. The significant effect of plate thickness on the buckling limit state is examined in this study. Results show that overstrength for these links (peak force divided by yield force) is between 1.2 and 4.5, with straight links producing larger overstrength. Additionally, proportioning the links to delay buckling, and designing the links to yield in the flexural mode are shown to improve energy dissipation.

Keywords

structural fuse / hysteretic damper / finite element analysis / energy dissipation / initial imperfection / butterfly-shaped links

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Alireza FARZAMPOUR, Matthew Roy EATHERTON. Parametric computational study on butterfly-shaped hysteretic dampers. Front. Struct. Civ. Eng., 2019, 13(5): 1214‒1226 https://doi.org/10.1007/s11709-019-0550-6

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Acknowledgments

This material is based upon the work supported by the National Natural Science Foundation (Grant No. CMMI-1453960). Any opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation or other sponsors. The Advanced Research Computing (ARC) facilities at Virginia Tech provided computational resources and technical support for this project.

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2019 Higher Education Press and Springer-Verlag GmbH Germany, part of Springer Nature
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