Empirical equations for the prediction of PGA and pseudo spectral accelerations using Iranian strong-motion data

2017 ◽  
Vol 22 (1) ◽  
pp. 263-285 ◽  
Author(s):  
H. Zafarani ◽  
Lucia Luzi ◽  
Giovanni Lanzano ◽  
M. R. Soghrat
Keyword(s):  
Strong Motion ◽  
Empirical Equations ◽  
Strong Motion Data ◽  
Motion Data ◽  
Spectral Accelerations ◽  
Pseudo Spectral

scholarly journals Towards preparation of design spectra for Serbian National Annex to Eurocode 8: Part I: spectral shapes and regional empirical equations for scaling pseudo-acceleration spectra

2012 ◽  
Vol 10 (2) ◽  
pp. 131-154
Author(s):  
Borko Bulajic ◽  
Miodrag Manic ◽  
Djordje Ladjinovic
Keyword(s):  
Ground Motion ◽  
Response Spectrum ◽  
Strong Motion ◽  
Soil Conditions ◽  
Eurocode 8 ◽  
Empirical Equations ◽  
Strong Motion Data ◽  
Motion Data ◽  
Local Soil ◽  
Spectral Shapes

Eurocode 8 allows that any country can use its own shape of the elastic response spectrum after it defines it in the National Annex. Having in mind that such country-specific spectra are to be derived through analysis of the strong motion data recorded in the considered seismo-tectonic region, in this Paper we discuss the existing and a set of new empirical equations for scaling pseudo-acceleration spectra in Serbia and the whole region of north-western Balkans. We then compare the presented spectra to those proposed by Eurocode 8. Results show that the indiscriminate use of the strong motion data from different seismo-tectonic regions, improper classification of the local soil conditions, and neglect of the effects of deep geology, may all lead to unreliable scaling equations and to extremely biased ground motion estimates. Moreover, only two spectral shapes that are defined for wide magnitude ranges and scaled by a single PGA value, are not able to adequately represent all important features of real strong ground motion, and instead of using such normalized spectra one should rather employ the direct scaling of spectral amplitudes that is based on the analysis of regionally gathered and processed strong motion data.

Processed strong-motion data for the El Salvador earthquake of June 19, 1982

1988 ◽  
Author(s):  
Kenneth W. Campbell ◽  
Sylvester Theodore Algermissen
Keyword(s):  
El Salvador ◽  
Strong Motion ◽  
Strong Motion Data ◽  
Motion Data

Duration prediction of Chilean strong motion data using machine learning

2021 ◽  
Vol 109 ◽  
pp. 103253
Author(s):  
Sarit Chanda ◽  
M.C. Raghucharan ◽  
K.S.K. Karthik Reddy ◽  
Vasudeo Chaudhari ◽  
Surendra Nadh Somala
Keyword(s):  
Machine Learning ◽  
Strong Motion ◽  
Strong Motion Data ◽  
Motion Data ◽  
Duration Prediction

Re-digitization of Strong Motion Data Recorded by SMAC-M Accelerographs

2021 ◽  
Vol 21 (1) ◽  
pp. 1_25-1_45
Author(s):  
Toshihide KASHIMA ◽  
Shin KOYAMA ◽  
Hiroto NAKAGAWA
Keyword(s):  
Strong Motion ◽  
Strong Motion Data ◽  
Motion Data

A comparison of two methods for earthquake source inversion using strong motion seismograms

1994 ◽  
Vol 37 (6) ◽  
Author(s):  
B. P. Cohee ◽  
G. C. Beroza
Keyword(s):  
Rise Time ◽  
Seismic Moment ◽  
Strong Motion ◽  
Rupture Time ◽  
Rupture Propagation ◽  
Rupture Velocity ◽  
Strong Motion Data ◽  
Motion Data ◽  
Inversion Methods ◽  
Window Method

In this paper we compare two time-domain inversion methods that have been widely applied to the problem of modeling earthquake rupture using strong-motion seismograms. In the multi-window method, each point on the fault is allowed to rupture multiple times. This allows flexibility in the rupture time and hence the rupture velocity. Variations in the slip-velocity function are accommodated by variations in the slip amplitude in each time-window. The single-window method assumes that each point on the fault ruptures only once, when the rupture front passes. Variations in slip amplitude are allowed and variations in rupture velocity are accommodated by allowing the rupture time to vary. Because the multi-window method allows greater flexibility, it has the potential to describe a wider range of faulting behavior; however, with this increased flexibility comes an increase in the degrees of freedom and the solutions are comparatively less stable. We demonstrate this effect using synthetic data for a test model of the Mw 7.3 1992 Landers, California earthquake, and then apply both inversion methods to the actual recordings. The two approaches yield similar fits to the strong-motion data with different seismic moments indicating that the moment is not well constrained by strong-motion data alone. The slip amplitude distribution is similar using either approach, but important differences exist in the rupture propagation models. The single-window method does a better job of recovering the true seismic moment and the average rupture velocity. The multi-window method is preferable when rise time is strongly variable, but tends to overestimate the seismic moment. Both methods work well when the rise time is constant or short compared to the periods modeled. Neither approach can recover the temporal details of rupture propagation unless the distribution of slip amplitude is constrained by independent data.

scholarly journals The INGV real time strong motion data sharing during the 2016 Amatrice (central Italy) seismic sequence

2016 ◽  
Vol 59 ◽  
Author(s):  
Marco Massa ◽  
Ezio D'Alema ◽  
Chiara Mascandola ◽  
Sara Lovati ◽  
Davide Scafidi ◽  
...  
Keyword(s):  
Real Time ◽  
Data Sharing ◽  
Strong Motion ◽  
Main Task ◽  
Seismic Sequence ◽  
Web Portal ◽  
Epicentral Area ◽  
Strong Motion Data ◽  
Motion Data ◽  
The Web

<p><em>ISMD is the real time INGV Strong Motion database. During the recent August-September 2016 Amatrice, Mw 6.0, seismic sequence, ISMD represented the main tool for the INGV real time strong motion data sharing.  Starting from August 24<sup>th</sup>,  the main task of the web portal was to archive, process and distribute the strong-motion waveforms recorded  by the permanent and temporary INGV accelerometric stations, in the case of earthquakes with magnitude </em><em>≥</em><em> 3.0, occurring  in the Amatrice area and surroundings.  At present (i.e. September 30<sup>th</sup>, 2016), ISMD provides more than 21.000 strong motion waveforms freely available to all users. In particular, about 2.200 strong motion waveforms were recorded by the temporary network installed for emergency in the epicentral area by SISMIKO and EMERSITO working groups. Moreover, for each permanent and temporary recording site, the web portal provide a complete description of the necessary information to properly use the strong motion data.</em></p>

scholarly journals Strong-motion data from the October 1, 1987 Whittier Narrows earthquake

1987 ◽  
Author(s):  
E.C. Etheredge ◽  
R.L. Porcella ◽  
R. P. with contributions from Maley ◽  
D. Johnson ◽  
M.J. Salsman ◽  
...  
Keyword(s):  
Strong Motion ◽  
Strong Motion Data ◽  
Motion Data
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