TY  - JOUR
A1  - Bindi, Dino
A1  - Kotha, Sreeram Reddy
A1  - Weatherill, Graeme
A1  - Lanzano, Giovanni
A1  - Luzi, Lucia
A1  - Cotton, Fabrice
T1  - The pan-European engineering strong motion (ESM) flatfile
BT  - consistency check via residual analysis
JF  - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering
N2  - We present the results of a consistency check performed over the flatfile extracted from the engineering strong motion (ESM) database. The flatfile includes 23,014 recordings from 2179 earthquakes in the magnitude range from 3.5 to 7.8 that occurred since the 1970s in Europe and Middle East, as presented in the companion article by Lanzano et al. (Bull Earthq Eng, 2018a). The consistency check is developed by analyzing different residual distributions obtained from ad-hoc ground motion prediction equations for the absolute spectral acceleration (SA), displacement and Fourier amplitude spectra (FAS). Only recordings from earthquakes shallower than 40 km are considered in the analysis. The between-event, between-station and event-and-station corrected residuals are computed by applying a mixed-effect regression. We identified those earthquakes, stations, and recordings showing the largest deviations from the GMPE median predictions, and also evaluated the statistical uncertainty on the median model to get insights on the applicable magnitude–distance ranges and the usable period (or frequency) range. We observed that robust median predictions are obtained up to 8 s for SA and up to 20 Hz for FAS, although median predictions for Mw ≥ 7 show significantly larger uncertainties with ‘bumps’ starting above 5 s for SA and below 0.3 Hz for FAS. The between-station variance dominates over the other residual variances, and the dependence of the between-station residuals on logarithm of Vs30 is well-described by a piece-wise linear function with period-dependent slopes and hinge velocity around 580 m/s. Finally, we compared the between-event residuals obtained by considering two different sources of moment magnitude. The results show that, at long periods, the between-event terms from the two regressions have a weak correlation and the overall between-event variability is dissimilar, highlighting the importance of magnitude source in the regression results.
KW  - Ground motion prediction equation
KW  - Residual analysis
KW  - European strong motion data
Y1  - 2018
U6  - https://doi.org/10.1007/s10518-018-0466-x
SN  - 1570-761X
SN  - 1573-1456
VL  - 17
IS  - 2
SP  - 583
EP  - 602
PB  - Springer
CY  - Dordrecht
ER  - 
TY  - JOUR
A1  - Bora, Sanjay Singh
A1  - Scherbaum, Frank
A1  - Kühn, Nicolas
A1  - Stafford, Peter
T1  - Fourier spectral- and duration models for the generation of response spectra adjustable to different source-, propagation-, and site conditions
JF  - Bulletin of earthquake engineering : official publication of the European Association for Earthquake Engineering
N2  - One of the major challenges related with the current practice in seismic hazard studies is the adjustment of empirical ground motion prediction equations (GMPEs) to different seismological environments. We believe that the key to accommodating differences in regional seismological attributes of a ground motion model lies in the Fourier spectrum. In the present study, we attempt to explore a new approach for the development of response spectral GMPEs, which is fully consistent with linear system theory when it comes to adjustment issues. This approach consists of developing empirical prediction equations for Fourier spectra and for a particular duration estimate of ground motion which is tuned to optimize the fit between response spectra obtained through the random vibration theory framework and the classical way. The presented analysis for the development of GMPEs is performed on the recently compiled reference database for seismic ground motion in Europe (RESORCE-2012). Although, the main motivation for the presented approach is the adjustability and the use of the corresponding model to generate data driven host-to-target conversions, even as a standalone response spectral model it compares reasonably well with the GMPEs of Ambraseys et al. (Bull Earthq Eng 3:1-53, 2005), Akkar and Bommer (Seismol Res Lett 81(2):195-206, 2010) and Akkar and Cagnan (Bull Seismol Soc Am 100(6):2978-2995, 2010).
KW  - Ground motion prediction equation
KW  - Fourier amplitude spectrum
KW  - Duration
KW  - Random vibration theory
KW  - Response Spectrum
Y1  - 2014
U6  - https://doi.org/10.1007/s10518-013-9482-z
SN  - 1570-761X
SN  - 1573-1456
VL  - 12
IS  - 1
SP  - 467
EP  - 493
PB  - Springer
CY  - Dordrecht
ER  -