Large-scale seismic assessment of RC buildings through rapid visual screening

被引:8
|
作者
Ahmed, Shaheryar [1 ]
Abarca, Andres [1 ]
Perrone, Daniele [2 ]
Monteiro, Ricardo [1 ]
机构
[1] Univ Sch Adv Studies IUSS Pavia, Pavia, Italy
[2] Univ Salento, Lecce, Italy
关键词
Seismic vulnerability; RC buildings; Rapid visual screening; Northern Algeria; Machine learning; RISK-ASSESSMENT; FRAGILITY;
D O I
10.1016/j.ijdrr.2022.103219
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Rapid urban growth, particularly in developing countries, is often accompanied by unplanned and highly vulnerable settlements which could lead to high seismic risk. This problem becomes even more pronounced when such developing countries are located in seismic prone regions, which, without a well-enforced seismic code, face high probability of major human and economic losses following a seismic event. With this in mind, large-scale rapid visual screening (RVS) procedures to perform seismic vulnerability assessment are of paramount importance to, at least, obtain a preliminary estimate of the risk to which buildings of a certain region are exposed to. RVS methods generally provide a seismic risk index based on the site hazard, the structural vulner-ability and the exposure. This paper presents one of many available RVS procedures, applied and assessed for large-scale seismic vulnerability mapping of a case-study province in Northern Algeria. Based on data collected during ad-hoc field surveys, the index-based selected RVS methodology was adapted to the reinforced concrete (RC) portion of the building portfolio, featuring over 2900 buildings, to estimate its seismic vulnerability. Taking advantage of a large amount of available data, a parametric study was then performed to understand the effect of the individual variables used in the RVS method on the vulnerability indices of the different buildings. The consistency of the method, as evi-denced by the results found across different building stock typologies, was also investigated to confirm the soundness of RVS approaches in large-scale assessments. Furthermore, in specific for the case-study region, the outcome of this study is extremely useful for preliminary identification of buildings (or building classes) more prone to earthquake damage and to assist decision-makers in planning seismic risk reduction strategies.
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页数:17
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