Macromodel-Based Simulation of Progressive Collapse: Steel Frame Structures
Publication: Journal of Structural Engineering
Volume 134, Issue 7
Abstract
Computationally efficient macromodels are developed for investigating the progressive collapse resistance of seismically designed steel moment frame buildings. The developed models are calibrated using detailed finite-element models of beam-column subassemblages and account for the most important physical phenomena associated with progressive collapse. The models are utilized to compare the collapse resistance of two-dimensional, ten-story steel moment frames designed for moderate and high seismic risk according to current design specifications and practices. The simulation results show that the frame designed for high seismic risk has somewhat better resistance to progressive collapse than the system designed for moderate seismic risk. The better performance is attributed to layout and system strength rather than the influence of improved ductile detailing. The alternate path method is shown to be useful for judging the ability of a system to absorb the loss of a critical member. However, it is pointed out that the method does not provide information about the reserve capacity of the system and so its results should be carefully evaluated.
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Acknowledgments
The presented work was supported in part by the Department of Civil and Environmental Engineering at the University of Michigan, the National Science Foundation (NSF) through Grant Nos. NSFCMS-0408243 and NSFCMS-0726493, and the NISTNational Institute of Standards and Technology. Any opinions, findings, conclusions, and recommendations expressed in this paper are those of the writers and do not necessarily reflect the views of the sponsors.
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Information & Authors
Information
Published In
Journal of Structural Engineering
Volume 134 • Issue 7 • July 2008
Pages: 1070 - 1078
Copyright
© 2008 ASCE.
History
Received: May 3, 2007
Accepted: Oct 3, 2007
Published online: Jul 1, 2008
Published in print: Jul 2008
Notes
Note. Associate Editor: Enrico Spacone
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