GNGTS 2018 - 37° Convegno Nazionale

GNGTS 2018 S essione 3.3 777 In this study, 320 waveform out of 2738 waveform in our database have been identified as pulse-shape signals. This study has found that 26 of the pulses occurred outside the region of PGV. We also checked where the impulse part occurred in the signal and which wavelet better explains the pulse region. 316 of the pulse-shaped signals are mimicked better by using a Ricker wavelet, whereas only 4 of them are mimicked better by using a 3rd order Morlet wavelet. A 4th order Morlet wavelet is not suitable to mimic any of the pulse-shape signals. Results can be seen in Table 1. At the end we have come up with the following conclusions: 1. Ricker wavelet analysis gives a higher resolution in the time domain, which is more suitable for determining the exact timing of the pulse. 2. A Ricker wavelet is better than Morlet wavelets for mimicking the pulse part of the earthquake signal based on residual analysis. 3. Our method is reproducing the spectral periods of the pulses, which makes the method convincing. 4. Most of the velocity pulses occurred at PGV. However, it is worth mentioning that pulses may occur also in other intervals of the signal. 5. This study has correlated with previous studies while expanding the information about the pulse shaped signal such as determining the pulse that occurred other than PGV region. References Abrahamson, N., Gregor, N., and Addo, K.; 2016: Bc hydro ground motion prediction equations for subduction earthquakes, Earthquake Spectra, 32(1), 23–44. Ancheta, T.D., Bozorgnia, Y., Darragh, R., Silva, W.J., Chiou, B., Stewart, J.P., Boore, D.M., Graves, R., Abrahamson, N.A., Campbell, K.W. and Idriss, I.M.; 2012. PEER NGA-West2 database: Adatabase of ground motions recorded in shallow crustal earthquakes in active tectonic regions. In Proceedings, 15th World Conference on Earthquake Engineering . Kalkan, E. and Kunnath, S. K.; 2006: Effects of fling step and forward directivity on seismic response of buildings, Earthquake spectra, 22(2), 367–390. Luzi, L., Puglia, R., Russo, E., D’Amico, M., Felicetta, C., Pacor, F., Lanzano, G., Çeken, U., Clinton, J., Costa, G. and Duni, L.; 2016. The engineering strong-motion database: A platform to access pan-European accelerometric data. Seismological Research Letters ,  87 (4), pp.987-997. Pacor, F., Paolucci, R., Luzi, L., Sabetta, F., Spinelli, A., Gorini, A., Nicoletti, M., Marcucci, S., Filippi, L. and Dolce, M.; 2011. Overview of the Italian strong motion database ITACA 1.0. Bulletin of Earthquake Engineering ,  9 (6), pp.1723-1739. Shahi, S. K. and Baker, J. W.; 2014: An efficient algorithm to identify strong-velocity pulses in multicomponent ground motions, Bulletin of the Seismological Society of America, 104(5), 2456–2466.