Rapid screening method for the determination of seismic vulnerability assessment of RC building stocks
العنوان: | Rapid screening method for the determination of seismic vulnerability assessment of RC building stocks |
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المؤلفون: | Onur Coskun, Mustafa Şahmaran, Alper Aldemir |
المصدر: | Bulletin of Earthquake Engineering. 18:1401-1416 |
بيانات النشر: | Springer Science and Business Media LLC, 2019. |
سنة النشر: | 2019 |
مصطلحات موضوعية: | 021110 strategic, defence & security studies, Hydrogeology, Computer science, Structural system, 0211 other engineering and technologies, Regression analysis, 02 engineering and technology, Building and Construction, Geotechnical Engineering and Engineering Geology, computer.software_genre, Visual inspection, Geophysics, Vulnerability assessment, Ordinary least squares, Linear regression, Screening method, Data mining, computer, Civil and Structural Engineering |
الوصف: | Until recently, seismic vulnerability assessment of large building inventories could only be done using rapid seismic assessment techniques. These techniques generally use some estimation variables whose status can be determined by visual inspection, and should therefore be well-trained to ensure sufficient accuracy. This study proposes a new rapid assessment method for reinforced concrete (RC) structures, developed based on the detailed assessment results of 545 RC structures. 400 of the available detailed assessment results were used to train the proposed rapid seismic assessment method. First, the estimation variables of the proposed method (i.e. number of stories, seismic zone, soil condition, building age, type of structural system, etc.) were selected. The penalty scores for these estimation variables were then determined using ordinary least square regression analysis and multi-variate linear regression analysis, successively. Finally, the remaining 145 RC buildings were used to test the performance of the proposed technique. The test showed that the overall correct estimation rate of the proposed method was as large as 83% for both databases. |
تدمد: | 1573-1456 1570-761X |
URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_________::1b67eca66568bf36683890ad4491b91b https://doi.org/10.1007/s10518-019-00751-9 |
حقوق: | CLOSED |
رقم الأكسشن: | edsair.doi...........1b67eca66568bf36683890ad4491b91b |
قاعدة البيانات: | OpenAIRE |
تدمد: | 15731456 1570761X |
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