Data-Based Probabilistic Damage Estimation for Asphalt Shingle Roofing
Publication: Journal of Structural Engineering
Volume 141, Issue 12
Abstract
Asphalt shingles on residential building roofs are susceptible to damage, and often blow off, during windstorms. The loss of shingles can also result in damage to the content in the interior of a residence by allowing the penetration of rain. This paper presents the data-based probabilistic damage estimation procedure to predict wind-induced damage on asphalt shingle roofing, using wind pressure data from wind tunnel testing. First, the probability distribution of peak wind pressure over a certain period for pressure data associated with each measurement tap is estimated. Then, the failure probability of the shingle associated with each tap and the damage ratio for the entire roofing shall be determined. Finally, a neural network is adopted to predict the wind-induced damage ratio for asphalt roof shingles considering multiple contributing factors such as wind speed, wind angle of attack, building sizes, roof slope, and terrain roughness.
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Acknowledgments
The support by the “Young Thousand Talents Program (China)” Special Research Found for the Doctoral Program of Higher Education (No. 20130184110009) is greatly acknowledged. The valuable comments and suggestions by reviewers are also greatly appreciated.
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© 2015 American Society of Civil Engineers.
History
Received: Jul 28, 2014
Accepted: Jan 30, 2015
Published online: May 5, 2015
Discussion open until: Oct 5, 2015
Published in print: Dec 1, 2015
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