Technical Papers
Feb 8, 2016

Stochastic Computational Model for Progressive Collapse of Reinforced Concrete Buildings

Publication: Journal of Structural Engineering
Volume 142, Issue 7

Abstract

A two-scale numerical model is developed to investigate the probabilistic collapse behavior of reinforced concrete (RC) buildings subjected to local structural damage. In this model, a set of coarse-scale cohesive elements is used to model the failure of potential damage zones in various RC structural members. The constitutive properties of the cohesive elements and their probability distributions are determined from detailed stochastic finite element simulations of the potential damage zones by taking into account the uncertainties in various material properties. The two-scale model is validated both experimentally and numerically for different structural subassemblages. The model is then applied to study the collapse behavior of a prototype 10-story RC building subjected to sudden column removal using both deterministic and probabilistic analysis frameworks. The deterministic calculation uses the mean material properties and the factored gravity loads according to the Unified Facilities Criteria (UFC) guidelines. The stochastic calculation considers uncertainties in both gravity loads and material properties, from which the occurrence probabilities of different collapse extents are determined. The results of the present probabilistic analysis are discussed in comparison with the existing deterministic approach, which reveals the important role of probabilistic methods in the analysis of progressive collapse.

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Acknowledgments

The authors acknowledge the Minnesota Supercomputing Institute at the University of Minnesota for providing computational resources for the numerical simulations presented in this paper.

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 142Issue 7July 2016

History

Received: May 24, 2015
Accepted: Nov 25, 2015
Published online: Feb 8, 2016
Published in print: Jul 1, 2016
Discussion open until: Jul 8, 2016

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Authors

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Bing Xue, S.M.ASCE
Ph.D. Candidate, Dept. of Civil, Environmental, and Geo-Engineering, Univ. of Minnesota, Minneapolis, MN 55455.
Jia-Liang Le, M.ASCE [email protected]
Assistant Professor, Dept. of Civil, Environmental, and Geo-Engineering, Univ. of Minnesota, Minneapolis, MN 55455 (corresponding author). E-mail: [email protected]

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