Correlation properties of integral ground-motion intensity measures from Italian strong-motion records

被引:15
|
作者
Huang, Chen [1 ]
Tarbali, Karim [1 ]
Galasso, Carmine [1 ,2 ]
机构
[1] UCL, Dept Civil Environm & Geomat Engn, London WC1E 6BT, England
[2] Scuola Univ Super IUSS Pavia, Classe Sci Tecnol & Soc, Pavia, Italy
来源
关键词
correlation; ground-motion models; integral intensity measures; Italian strong-motion records; CUMULATIVE ABSOLUTE VELOCITY; ARIAS INTENSITY; PREDICTION EQUATIONS; SIGNIFICANT DURATION; SPATIAL CORRELATION; EMPIRICAL CORRELATIONS; SPECTRAL ACCELERATION; SEISMIC INTENSITY; MODELS; SITE;
D O I
10.1002/eqe.3318
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study investigates the correlation properties of integral ground-motion intensity measures (IMs) from Italian strong-motion records. The considered integral IMs include 5-95% significant duration, Housner intensity, cumulative absolute velocity, and Arias intensity. Both IM spatial correlation and the correlation between different integral and amplitude-based IMs (i.e., cross-IM correlation) are addressed in this study. To this aim, a new Italian ground-motion model (GMM) with spatial correlation for integral IMs is first introduced. Based on the newly developed GMM, the empirical correlation coefficients from interevent and intraevent residuals are investigated and various analytical correlation models between integral IMs and amplitude-based IMs are proposed. The effective range parameter representing spatial correlation properties and the trend in the cross-IM correlations are compared with existing models in the literature. The variability of the effective range parameters with respect to event-specific features is also discussed. Modeling ground-motion spatial and cross-IM correlations is an important step in seismic hazard and risk assessment of spatially distributed systems. Investigating region-specific correlation properties based on Italian strong-motion records is of special interest as several correlation models have been developed based on global datasets, often lacking earthquakes in extensional regions such as Italy.
引用
收藏
页码:1581 / 1598
页数:18
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