Uncertainties in Predicting Structural Disproportionate Collapse

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Title: Uncertainties in Predicting Structural Disproportionate Collapse

Author(s): Shalva Marjanishvili and Serdar Astarlioglu

Publication: Special Publication

Volume: 309

Issue:

Appears on pages(s): 1-12

Keywords: robustness, uncertainty, reliability; disproportionate collapse; column loss; alternate path method, probabilistic modeling

Date: 6/1/2016

Abstract:
The possibility of a local structural failure causing global collapse of a structural system has fueled the continued development of improved computational methods to model building behavior, as well as "best practices" engineering standards. In spite of these efforts, recent events are bringing the issue of collapse prevention to the forefront and highlighting the shortcomings of existing design practices. The catastrophic nature of structural collapse dictates the need for more reliable methodologies to quantify the likelihood of structural failures, and strategies to minimize potential consequences. This paper presents the results of a stochastic nonlinear dynamic analysis study of a simple reinforced concrete structural model to predict catastrophic failure. The performed analysis indicates that, at the point of incipient failure, uncertainties caused by the variability of the design parameters become increasingly large. Consequently, it may not be possible to accurately predict when (and if) failure may occur. Recognizing the need to understand uncertainties associated with risk and probabilities of unlikely events (low probability and high consequence events), this paper sets the stage to better understand the limitations of current numerical analysis methods and discuss innovative alternatives.