In this work, we analyze the records of the Italian strong motion database (ITACA, http://itaca.mi.ingv.it) with the aim of identifying stations affected by site effects that are not captured by standard seismic classification schemes. In particular, we consider four different site classifications, two of them based on geological/geophysical characteristics and two driven by data. For each classification we develop a ground motion prediction equation using a random effect approach to isolate the between-station and within-station distribution of errors. The site coefficients obtained for the different classes confirm that site amplification effects are significant for both the horizontal and vertical components. The between-station error normalized to the standard deviation of the between-station error distribution is then used to identify stations characterized by large errors, attributable to site effects not accounted for by the classification schemes. The results show that large errors can affect the predictions when the site effects are not uniquely related to the reduction of the seismic impedance in the uppermost layers. For example, amplifications of ground motion over the long period range are observed for stations installed within alluvial closed-shape basins, as consequence of locally generated surface waves. For these stations, classifications based on the horizontal to vertical response spectra ratio are not reliable, since amplifications are also affecting the vertical component. Another interesting feature which emerges from the analysis is the significant de-amplification of short period spectral ordinates that seems to be related to stations typically set in at the foundation level of massive structures. To increase the usefulness of the data set, the most important distinctive features of the strong motion stations are documented in the ITACA database reports containing the instrument information and the available geological-geotechnical data.
Identification of accelerometric stations in ITACA with distinctive features in their seismic response.
PAOLUCCI, ROBERTO
2011-01-01
Abstract
In this work, we analyze the records of the Italian strong motion database (ITACA, http://itaca.mi.ingv.it) with the aim of identifying stations affected by site effects that are not captured by standard seismic classification schemes. In particular, we consider four different site classifications, two of them based on geological/geophysical characteristics and two driven by data. For each classification we develop a ground motion prediction equation using a random effect approach to isolate the between-station and within-station distribution of errors. The site coefficients obtained for the different classes confirm that site amplification effects are significant for both the horizontal and vertical components. The between-station error normalized to the standard deviation of the between-station error distribution is then used to identify stations characterized by large errors, attributable to site effects not accounted for by the classification schemes. The results show that large errors can affect the predictions when the site effects are not uniquely related to the reduction of the seismic impedance in the uppermost layers. For example, amplifications of ground motion over the long period range are observed for stations installed within alluvial closed-shape basins, as consequence of locally generated surface waves. For these stations, classifications based on the horizontal to vertical response spectra ratio are not reliable, since amplifications are also affecting the vertical component. Another interesting feature which emerges from the analysis is the significant de-amplification of short period spectral ordinates that seems to be related to stations typically set in at the foundation level of massive structures. To increase the usefulness of the data set, the most important distinctive features of the strong motion stations are documented in the ITACA database reports containing the instrument information and the available geological-geotechnical data.File | Dimensione | Formato | |
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