Application of Statistical Random Sampling and Bayesian Updating in Planning for Terra-Cotta Façade Inspection
Publication: Journal of Architectural Engineering
Volume 23, Issue 2
Abstract
In this paper, an application of statistical random sampling and probabilistic Bayesian updating for planning building façade inspection is introduced. The application method presented is specifically for façades made up of terra-cotta blocks, for which a mode of damage is deterioration in their metal anchors as a result of corrosion. Using this method, an initial probability distribution for the proportion of blocks with damaged metal anchors is assumed; a limited number of blocks is then randomly selected, the blocks are removed, and the state of damage in their metal anchors is investigated. Based on the results of this initial investigation, a Bayesian approach is used for updating information on the proportion of blocks with damaged metal anchors to modify the damage probability distribution, and a damage index is then introduced, based on the updated results. This index can be used as a decision-making tool in determining the state of the health of the façade and planning for the next step in further investigations of the condition of terra-cotta blocks. The presented method is a planning tool that can be used by architects and engineers in an effort to optimize the cost associated with opening blocks for inspection.
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Acknowledgments
The authors express their gratitude to Arthur Kurzydlo of Dearborn Engineering Corporation, Chicago for providing information on the case study presented.
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© 2016 American Society of Civil Engineers.
History
Received: Jun 2, 2016
Accepted: Oct 20, 2016
Published online: Dec 6, 2016
Discussion open until: May 6, 2017
Published in print: Jun 1, 2017
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