Impact of vulnerability assumptions and input parameters in urban seismic risk assessment

被引:0
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作者
M. C. Hoyos
A. F. Hernández
机构
[1] Independent Seismic Risk Consultant,ISTerre
[2] Université Grenoble Alpes,undefined
来源
关键词
Local seismic analysis; Seismic risk assessment; Hazard-consistent structural vulnerability; Sensitivity analysis; Open-source data;
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学科分类号
摘要
This study addresses some critical issues in the selection of input data for probabilistic seismic risk assessment at a local scale, considering available open-source information. It focuses on the derivation of vulnerability curves, which should be consistent with the local hazard and building practices, analysing the effect of (1) the record selection methodology, (2) the regression procedure followed for the analytical vulnerability derivation and (3) the consideration or not of local structural characteristics in the modelling process. It illustrates the significant differences in the results when distinct assumptions and sources of information—global, regional, or local—are used for the analysis. Based on a case study in Medellin, Colombia for assets representing the most vulnerable building classes in the city (unreinforced masonry houses and low code reinforced concrete buildings), accounting for more than 60% of its building stock, the effects of the previously mentioned parameters are studied. It is shown that hazard-consistent record selection is extremely important in the derivation of vulnerability models to use at a local scale, for sites with contributions from different tectonic regimes. Considerable variability is found in risk metrics such as Probable Maximum Loss curves and Average Annual Loss Ratios, rendering crucial the communication to decision-makers of these assumptions and the bias they could generate. Given the hazard characteristics of the site (with common low intensity events) it was seen that the lower tails of vulnerability curves have a large impact in loss results and should be given special attention.
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页码:4407 / 4434
页数:27
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