scholarly journals Strong Motion Data of Intensity Seismometer (Shindo-kei) during the West off Fukuoka Earthquake of 2005 and Their Structural Damage Potential

2007 ◽  
Vol 7 (2) ◽  
pp. 190-204
Author(s):  
Hiroshi KAWASE
Keyword(s):  
Structural Damage ◽  
Strong Motion ◽  
Damage Potential ◽  
The West ◽  
Strong Motion Data ◽  
Motion Data

Use of Wavelet-Based Damage-Sensitive Features for Structural Damage Diagnosis Using Strong Motion Data

2011 ◽  
Vol 137 (10) ◽  
pp. 1215-1228 ◽  
Author(s):  
Hae Young Noh ◽  
K. Krishnan Nair ◽  
Dimitrios G. Lignos ◽  
Anne S. Kiremidjian
Keyword(s):  
Structural Damage ◽  
Strong Motion ◽  
Damage Diagnosis ◽  
Strong Motion Data ◽  
Motion Data

scholarly journals Constraints on the location of the 2008, MW 6.4 Achaia-Ilia earthquake fault from strong motion data.

2016 ◽  
Vol 47 (3) ◽  
pp. 1231
Author(s):  
Z. Roumelioti ◽  
N. Theodoulidis ◽  
M. Bouchon
Keyword(s):  
Ground Surface ◽  
Strong Motion ◽  
Fault Models ◽  
S Wave ◽  
Seismogenic Fault ◽  
The West ◽  
Strong Motion Data ◽  
Motion Data ◽  
Imaginary Line ◽  
Discrete Wavenumber Method

The June 2008, Mw6.4 Achaia-Ilia earthquake was the first recorded dextral strikeslip event of considerable magnitude in western Peloponnese, which, nevertheless, could not be related to any of the known/mapped structures at the ground surface. Published locations of the mainshock focus by various agencies/researchers differ by as much as 6 km and 16 km in the horizontal and vertical dimensions, respectively, making even more difficult the accurate siting of the seismogenic fault. However, the 2008 earthquake provided a valuable set of near-fault strong motion data, which could shed some light on the problem of accurately locating the earthquake source. To this end, we use the discrete wavenumber method to forward model the strongground motion records at three stations, located close to the prolongation of the 2008 strike. We test different locations and lengths for the ruptured plane and compare synthetic polarities and amplitudes of the first strong S-wave pulse to actual data. We conclude that the line of maximum moment release (our fault models are vertical planes) during the 2008 earthquake is located to the east of the imaginary line connecting stations PAT2 and AMAA and to the west of station PYR1. 

scholarly journals The 30 October 2020, Mw 7.0, Samos Earthquake: Aftershock Relocation, Slip Model, Coulomb Stress Evolution and Estimation of Shaking

2021 ◽  
Author(s):  
Konstantinos Lentas ◽  
Charikleia Gkarlaouni ◽  
Nikos Kalligeris ◽  
NIKOLAOS S. MELIS
Keyword(s):  
Strong Motion ◽  
Aftershock Sequence ◽  
Coulomb Stress ◽  
Slip Model ◽  
Stress Evolution ◽  
The West ◽  
Strong Motion Data ◽  
Motion Data ◽  
The North ◽  
Stress Changes

Abstract We study the major Mw 7.0, 30 October 2020, Samos earthquake and its aftershocks, by calculating improved locations using differential travel times and waveform cross-correlations.We image the rupture of the mainshock using local strong motion data, and we examine the Coulomb stress evolution prior to the mainshock, as well as the coseismic stress changes. Lastly, we estimate the produced shaking using all the available information from strong motion data and testimonies. Earthquake relocations reveal the activation of the E-W oriented, Kaystrios fault, in the North basin of Samos with a possible extension to the West. The kinematic rupture inversion suggests non-uniform bilateral rupture on a ~60 km × ~20 km fault area, with the main rupture propagating towards the West and maximum slip up to approximately 2.5 m. Improved locations of the aftershock sequence are anti-correlated with areas of maximum slip on the fault surface. Similarly, the Coulomb stress change calculations show that only off-fault earthquake clusters are located within lobes of increasing positive static stress changes. This observation is consistent with assuming a fault area of either uniform slip, or variable slip according to the obtained slip model. Both scenarios indicate typical stress patterns for a normal fault with E-W orientation, with stress lobes of positive ΔCFF increments expanding in E-W orientation. In the case of the variable slip model, both negative and positive stress changes show slightly larger values compared to the uniform slip model. Finally, Modified Mercalli Intensities based on the fault model obtained in this study indicate maximum intensity (VII+) in the North Samos island. Spectral acceleration values at 0.3 s period also demonstrate the damaging situation at Izmir.

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.

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