Seismic Debris Field for Collapsed RC Moment Resisting Frame Buildings
Publication: Journal of Structural Engineering
Volume 147, Issue 5
Abstract
The debris field of earthquake-induced building collapse can block or reduce the capacity of adjacent sidewalks and roads, hinder emergency and evacuation operations, and therefore adversely influence the seismic resilience of a community. To consider the influence that earthquake-induced building collapse can have on mobility after an earthquake, the seismic debris field generated from the collapse of prototype reinforced-concrete (RC) moment resisting frame buildings with different heights is characterized using a validated applied element method (AEM) computational model. A deep neural network (DNN) is used to classify the mode of collapse of the prototype buildings based on a set of input parameters related to the properties of the applied ground motion record and the building height. The DNN is able to predict the collapse mode of the studied prototype building with an accuracy of 92% and 82% for the training and test datasets, respectively. The extent of the debris field around the collapsed buildings is then characterized probabilistically. It is shown that the extent of the debris field does not depend on the design code used to proportion the buildings. Based on the simulation results, an expression that captures the extent of the debris field as a function of building height is developed.
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Data Availability Statement
All data, models, and code generated or used during the study appear in the published article.
Acknowledgments
This work was supported by the University of Michigan and the US National Science Foundation (NSF) through Grant No. ACI-1638186. Any opinions, findings, conclusions, and recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the sponsors.
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Published In
Journal of Structural Engineering
Volume 147 • Issue 5 • May 2021
Copyright
© 2021 American Society of Civil Engineers.
History
Received: Jun 8, 2020
Accepted: Dec 11, 2020
Published online: Feb 24, 2021
Published in print: May 1, 2021
Discussion open until: Jul 24, 2021
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