Collapse Simulations of Steel-Concrete Composite Floors under Column Loss Scenarios
Publication: Journal of Structural Engineering
Volume 146, Issue 12
Abstract
Characterizing structural resiliency after severe damage to a few load-carrying members is challenging. Engineers use various computational approaches to assess the vulnerability of structures and to evaluate the parameters that affect their response. Few of these approaches are capable of predicting the actual peak load-carrying capacity a damaged structure can withstand before experiencing total collapse, and practically none of them have been verified against actual test results. In this paper, experimental data from large-scale tests on steel–concrete composite floor systems under different column loss scenarios were used to develop and to validate a high-fidelity numerical modeling approach capable of predicting the response of the tests up to total collapse. This approach incorporates geometric and material nonlinearity, explicit modeling of steel and concrete failure, and contact modeling using LS-DYNA version R10.2.0. Nearly all specimen components were modeled using brick elements, including the concrete slab, steel members, bolts, and other connecting elements. The corrugated metal decking was represented with shell elements, and beam elements represent the reinforcing steel and shear studs. The predicted response and ultimate load–carrying capacity up to total collapse show good agreement with the results of the experimental tests. Validating the numerical models revealed the sensitivity of various modeling parameters and demonstrated the potential for inaccurate predictions of response when certain parameters were not correctly specified. The most important of these parameters are described in this manuscript. Lessons learned from the current study are helpful for understanding the mechanisms that have the greatest impact on collapse of composite floor systems, and these lessons can be used to gain insight on the collapse potential of other structures with different geometries or configurations.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are proprietary or confidential in nature and may only be provided with restrictions:
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Experimental data.
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Numerical models (limited access may be provided upon request to the first author).
Acknowledgments
The research presented in this paper is based upon work supported by the Science & Technology Directorate, US Department of Homeland Security (DHS), under Award No. 2010-ST-108-000014. The authors thank the Department of Homeland Security for their support of this research program. The views and conclusions contained in this document are those of the authors and should not be interpreted as necessarily representing official policies, either expressed or implied, of the US Department of Homeland Security. The authors also gratefully acknowledge Valley Joist, Inc., for their donation of the steel floor decking, and also thank the Steel Deck Institute for their assistance with this project. The authors gratefully acknowledge the contributions of Prof. Bassam Izzuddin from Imperial College and his research assistant Dr. Hamed Zolghadr Jahromi for providing computational modeling support during this research effort. Engineers from Protection Engineering Consultants provided valuable insight on current progressive collapse design guidelines as well as the selected testing methodology. Mark Waggoner from Walter P Moore was instrumental in providing guidance on current structural engineering design practice. Finally, this project would not have been possible without the assistance provided by the technical staff at the Phil M. Ferguson Structural Engineering Laboratory and the following graduate research assistants at The University of Texas at Austin: Sean Donahue, Georgios Moutsanidis, Lindsay A. Hull, and Umit C. Oksuz.
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Published In
Journal of Structural Engineering
Volume 146 • Issue 12 • December 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Jan 9, 2020
Accepted: Jun 24, 2020
Published online: Sep 24, 2020
Published in print: Dec 1, 2020
Discussion open until: Feb 24, 2021
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