Data-Based Probabilistic Damage Estimation for Asphalt Shingle Roofing

被引:26
|
作者
Huang, Guoqing [1 ]
He, Hua [2 ]
Mehta, Kishor C. [3 ]
Liu, Xiaobo [4 ]
机构
[1] Southwest Jiaotong Univ, Sch Civil Engn, Chengdu 610031, Peoples R China
[2] Munich Reinsurance, Beijing Branch, Beijing 100022, Peoples R China
[3] Natl Sci Fdn, Arlington, VA 22230 USA
[4] Southwest Jiaotong Univ, Sch Math, Chengdu 610031, Peoples R China
关键词
Wind-induced damage; Asphalt shingle; Translation process model; Hermite polynomial model; Damage ratio; Neural network; Wind effects; WIND LOADS; BUILDINGS; PRESSURE;
D O I
10.1061/(ASCE)ST.1943-541X.0001300
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
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. (C) 2015 American Society of Civil Engineers.
引用
收藏
页数:10
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