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首页> 外文会议>Innovation, practice, safety >COMPARISON OF OBSERVED DAMAGE WITH RESULTS FROM ANALYTICAL SIMULATION MODELS. THE CASE OF JULY 9, 1998, FAIAL EARTHQUAKE IN THE AZORES
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COMPARISON OF OBSERVED DAMAGE WITH RESULTS FROM ANALYTICAL SIMULATION MODELS. THE CASE OF JULY 9, 1998, FAIAL EARTHQUAKE IN THE AZORES

机译：观察到的损伤与分析模拟模型结果的比较。以1998年7月9日亚速尔群岛发生大地震为例

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摘要

The July 9, 1998 earthquake that struck Faial, Pico and S?o Jorge Islands in the Azores archipelago provided a large amount of information which permits the validation of damage scenarios simulators. Ten years later and integrated on the project FCT-POCI/CTE-GIN/58095/2004 "USuET -Urban System under Earthquake Threat", we are able to recreate earthquake effects in the urban areas that comprise about 3000 buildings using data collected during the reconstruction period (1998-2007). Based on a post-inspection of building files, a database was compiled with typology classification, damage description, reconstruction techniques and costs of intervention.For this stock of housing we developed a damage scenario simulator using the empirical vulnerability methods of the EMS-98 macroseismic scale as well as vulnerability obtained through mechanical modelling of a few typologies. The influence of the soil layers (geological and geomorphologic effects) were also taken into account as part of the attenuation process.The aim of present article is to compare values, in terms of number of collapsed houses and mean damage grade obtained by the seismic simulator with those verified on July 9, 1998, and update the analytical models in order to reduce the error between model results and observed values.
机译：1998年7月9日地震袭击了亚速尔群岛的Faial，Pico和S？o Jorge群岛，提供了大量信息，可用于验证破坏情景模拟器。十年后，我们将其纳入FCT-POCI / CTE-GIN / 58095/2004项目“地震威胁下的美国城市系统”，利用地震期间收集的数据，我们能够在约3000座建筑物中重现市区的地震影响。重建期（1998年至2007年）。在对建筑文件进行事后检查的基础上，编译了一个数据库，其中包括类型分类，损坏描述，重建技术和干预成本。针对这批住房，我们使用EMS-98宏观地震经验易损性方法开发了一个损坏情景模拟器。规模以及通过几种类型的机械建模获得的脆弱性。作为衰减过程的一部分，还考虑了土壤层的影响（地质和地貌效应）。本文旨在比较地震模拟器获得的倒塌房屋数量和平均破坏等级方面的值与1998年7月9日验证的数据进行比较，并更新分析模型，以减少模型结果与观测值之间的误差。

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