Statistical modelling of seismic vulnerability of RC, timber and masonry buildings from complete empirical loss data

被引:19
作者
Bessason, Bjarni [1 ]
Bjarnason, Jon Orvar [2 ]
Rupakhety, Rajesh [1 ]
机构
[1] Univ Iceland, Fac Civil & Environm Engn, Hjardarhagi 2, IS-107 Reykjavik, Iceland
[2] Nat Catastrophe Insurance Iceland, Hlidarsmari 14, IS-201 Kopavogur, Iceland
关键词
Seismic vulnerability; Zero-inflated beta model; Beta regression; RC buildings; Timber buildings; Masonry buildings; BETA REGRESSION; DAMAGE DATA; EARTHQUAKES; ICELAND;
D O I
10.1016/j.engstruct.2019.109969
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In June 2000 two shallow, strike slip, Mw6.5 earthquakes occurred in the middle of the largest agricultural region in Iceland. The epicentres were close to small towns and villages and almost 5000 residential buildings were affected. A great deal of damage occurred but no residential buildings collapsed and there was no loss of life. Insurance against natural disasters is compulsory for all buildings in Iceland and they are all registered in a comprehensive official property database. Therefore, to fulfil insurance claims, a field survey was carried out after the two earthquakes where repair cost was estimated for every damaged building. By combing the loss data with the property database it was possible to establish a complete loss database, where all residential buildings in the affected area were included, both buildings with loss as well as buildings with no-loss. The main aim of the study was to fit a statistical vulnerability model to the data. Due to the high proportion of no-loss buildings in the database (similar to 84%) a new and novel vulnerability model was used based on a zero-inflated beta regression model. The model was fitted to the three main building typologies in the affected region, i.e. low-rise structural wall RC, timber, and masonry buildings. The proposed model can be used to predict the mean and desired prediction limits of the losses for a given intensity level as well as to create fragility functions. All the typologies showed outstanding performance in the two destructive earthquakes, which is important to report, model and learn from.
引用
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页数:12
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