scholarly journals Seismological and Engineering Characteristics of Strong Motion Data from 24 and 26 September 2019 Marmara Sea Earthquakes

2021 ◽  
Author(s):  
Fatma Sevil Malcıoğlu ◽  
Hakan Süleyman ◽  
Eser Çaktı
Keyword(s):  
Ground Motion ◽  
Prediction Models ◽  
Strong Motion ◽  
P Wave ◽  
Corner Frequency ◽  
Marmara Region ◽  
Marmara Sea ◽  
S Wave ◽  
Data Set ◽  
Motion Data

Abstract An MW 4.5 earthquake took place on September 24, 2019 in the Marmara Sea. Two days after, on September 26, 2019, Marmara region was rattled by an MW5.7 earthquake. With the intention of compiling an ample strong ground motion data set of recordings, we have utilized the stations of Istanbul Earthquake Rapid Response and Early Warning System operated by the Department of Earthquake Engineering of Boğaziçi University and of the National Strong Motion Network operated by AFAD. All together 438 individual records are used to calculate the source parameters of events; namely, corner frequency, radius, rupture area, average source dislocation, source duration and stress drop. Some of these parameters are compared with empirical relationships and discussed extensively. Duration characteristics are analyzed in two steps; first, by making use of the time difference between P-wave and S-wave onsets and then, by considering S-wave durations and significant durations. It is observed that they yield similar trends with global models. PGA, PGV and SA values are compared with three commonly used ground motion prediction models. At distances closer than about 60 km observed intensity measures mostly conform with the GMPE predictions. Beyond 60 km their attenuation is clearly faster than those of GMPEs. Frequency-dependent Q models are developed for both events. Their consistency with existing regional models are confirmed.

SEISMOLOGICAL AND ENGINEERING PARAMETERS OF 24 and 26 SEPTEMBER, 2019 MARMARA SEA EARTHQUAKES

2020 ◽  
Author(s):  
Eser Çakti ◽  
Fatma Sevil Malcioğlu ◽  
Hakan Süleyman
Keyword(s):  
Earthquake Engineering ◽  
Prediction Models ◽  
Source Parameters ◽  
Strong Motion ◽  
P Wave ◽  
Corner Frequency ◽  
Marmara Sea ◽  
S Wave ◽  
Data Set ◽  
The North

<p>On 24<sup>th</sup> and 26<sup>th</sup>  September 2019, two earthquakes of M<sub>w</sub>=4.5 and M<sub>w</sub>=5.6 respectively took place in the Marmara Sea. They were associated with the Central Marmara segment of the North Anatolian Fault Zone, which is pinpointed by several investigators as the most likely segment to rupture in the near future giving way to an earthquake larger than M7.0. Both events were felt widely in the region. The M<sub>w</sub>=5.6 event, in particular, led to a number of building damages in Istanbul, which were larger than expected in number and severity. There are several strong motion networks in operation in and around Istanbul. We have compiled a data set of recordings obtained at the stations of the Istanbul Earthquake Rapid Response and Early Warning operated by the Department of Earthquake Engineering of Bogazici University and of the National Strong Motion Network operated by AFAD. It consists of 148 three component recordings, in total.  444 records in the data set, after correction, were analyzed to estimate the source parameters of these events, such as corner frequency, source duration, radius and rupture area, average source dislocation and stress drop. Duration characteristics of two earthquakes were analyzed first by considering P-wave and S-wave onsets and then, focusing on S-wave and significant durations. PGAs, PGVs and SAs were calculated and compared with three commonly used ground motion prediction models (i.e  Boore et al., 2014; Akkar et al., 2014 and Kale et al., 2015). Finally frequency-dependent Q models were estimated using the data set and their validity was dicussed by comparing with previously developed models.</p>

On Scaling of Earthquake Rise‐Time Estimates

2019 ◽  
Vol 109 (6) ◽  
pp. 2741-2745
Author(s):  
Alexander A. Gusev ◽  
Danila Chebrov
Keyword(s):  
Ground Motion ◽  
Strong Motion ◽  
Scaling Behavior ◽  
Corner Frequency ◽  
Source Spectrum ◽  
Self Similarity ◽  
Data Set ◽  
Motion Data ◽  
Time Estimates ◽  
Earthquake Ruptures

Abstract The scaling behavior of rise times Tr determined within earthquake source inversions that used strong‐motion data is determined using estimates as accumulated in the SRCMOD database. The Tr versus M0 trend derived from this data set is close to logTr=1/3logM0+ const; this agrees with the assumption of self‐similarity of earthquake ruptures. No biasing effect of station distance on Tr was found. The result was compared to recent scaling estimates based on mass teleseismic inversions. Absolute levels of teleseismic and local inversions match well; the slope of the trend of teleseismic estimates is somewhat more gradual. The absolute levels of Tr versus M0 trends recovered from finite source inversions may need reduction when used to predict parameters of near‐source ground motion. The observed scaling behavior of Tr is incompatible with the assumption that Tr defines the second corner frequency of the source spectrum.

NGA Project Strong-Motion Database

2008 ◽  
Vol 24 (1) ◽  
pp. 23-44 ◽  
Author(s):  
Brian Chiou ◽  
Robert Darragh ◽  
Nick Gregor ◽  
Walter Silva
Keyword(s):  
Time Series ◽  
Ground Motion ◽  
Model Development ◽  
Strong Motion ◽  
Corner Frequency ◽  
Engineering Practice ◽  
Data Set ◽  
Acceleration Time ◽  
Crustal Earthquakes ◽  
Strong Motion Database

A key component of the NGA research project was the development of a strong-motion database with improved quality and content that could be used for ground-motion research as well as for engineering practice. Development of the NGA database was executed through the Lifelines program of the PEER Center with contributions from several research organizations and many individuals in the engineering and seismological communities. Currently, the data set consists of 3551 publicly available multi-component records from 173 shallow crustal earthquakes, ranging in magnitude from 4.2 to 7.9. Each acceleration time series has been corrected and filtered, and pseudo absolute spectral acceleration at multiple damping levels has been computed for each of the 3 components of the acceleration time series. The lowest limit of usable spectral frequency was determined based on the type of filter and the filter corner frequency. For NGA model development, the two horizontal acceleration components were further rotated to form the orientation-independent measure of horizontal ground motion (GMRotI50). In addition to the ground-motion parameters, a large and comprehensive list of metadata characterizing the recording conditions of each record was also developed. NGA data have been systematically checked and reviewed by experts and NGA developers.

Strong-Motion Accelerograms of the Oroville, California, aftershocks: Data processing and the aftershock of 0350 August 6, 1975

1980 ◽  
Vol 70 (1) ◽  
pp. 243-267
Author(s):  
Jon B. Fletcher ◽  
A. Gerald Brady ◽  
Thomas C. Hanks
Keyword(s):  
Ground Motion ◽  
Stress Drop ◽  
Seismic Moment ◽  
Strong Motion ◽  
P Wave ◽  
S Wave ◽  
Quality Of Data ◽  
Pass Filter ◽  
Processing Scheme ◽  
Field Source

abstract The Oroville aftershock accelerograms are characterized by short durations (≲2 sec) of strong ground motion, small S-wave minus trigger times (≲2 sec), and an enrichment in frequencies above 1 Hz, as might be expected for 3 ≲ M ≲5 earthquakes recorded at close distances (R ≲ 15 km). These characteristics introduce significant error into the velocity and displacement traces calculated according to the routine procedures used in the series “Strong Motion Earthquake Accelerograms.” These errors are markedly reduced by removing all decimation in the processing scheme and by constructing a smoother response for the Ormsby high-pass filter. The result is an accurate set of velocity and displacement traces that can be used in a wide variety of source-mechanism and ground-motion studies. These revised processing procedures are applied to the ten strong-motion accelerograms of one of the largest aftershocks (0350 August 6, 1975; ML = 4.7) to illustrate the quality of data available for 12 such well-recorded aftershocks and to estimate the source properties of this particular earthquake. All of the accelerographs triggered on the P wave, allowing the recovery of the complete S wave on ten accelerograms. Offsets in displacement across the S wave and a ramp-like signature leading up to the S wave identified on the displacement traces are apparently near-field source effects. The seismic moment and stress drop determined for this normal faulting event are 4.0 × 1023 dyne-cm, and 410 bars, respectively. The seismic moment and stress drop are determined by averaging individual measurements at 9 and 8 stations, respectively, and are well-constrained with standard deviations that are about 25 per cent of the mean.

A theoretical study of the radiation from small strikeslip earthquakes at close distances

1983 ◽  
Vol 73 (1) ◽  
pp. 83-96 ◽  
Author(s):  
Michel Campillo ◽  
Michel Bouchon
Keyword(s):  
Ground Motion ◽  
Epicentral Distance ◽  
Homogeneous Medium ◽  
Source Model ◽  
Strike Slip ◽  
Peak Ground Velocity ◽  
Corner Frequency ◽  
Crack Model ◽  
Sharp Change ◽  
S Wave

abstract We present a study of the seismic radiation of a physically realistic source model—the circular crack model of Madariaga—at close distance range and for vertically heterogeneous crustal structures. We use this model to represent the source of small strike-slip earthquakes. We show that the characteristics of the radiated seismic spectra, like the corner frequency, are strongly affected by the presence of the free surface and by crustal layering, and that they can be considerably different from the ones of the homogeneous-medium far-field solution. The vertical and radial displacement spectra are the most strongly affected. We use this source model to calculate the decay of peak ground velocity with epicentral distance and source depth for small strike-slip earthquakes in California. For distances between 10 and 80 km, the peak horizontal velocity decay is of the form r−1.25 for a 4-km hypocentral depth and r−1.65 for deeper sources. The predominance of supercritically reflected arrivals beyond epicentral distances of 70 to 80 km produces a sharp change in the rate of decay of the ground motion. For most of the cases considered, the peak ground velocity increases between 80 and 100 km. We also show that the S-wave velocity in the source layer is the lower limit of phase velocities associated with significant ground motion.

Retrieval of source-extent parameters and the interpretation of corner frequency

1983 ◽  
Vol 73 (6A) ◽  
pp. 1499-1511
Author(s):  
Paul Silver
Keyword(s):  
Body Wave ◽  
Amplitude Spectrum ◽  
Low Frequency ◽  
P Wave ◽  
Corner Frequency ◽  
S Wave ◽  
Dislocation Source ◽  
Statistical Measures ◽  
Dislocation Models ◽  
Planar Dislocation

Abstract A method is proposed for retrieving source-extent parameters from far-field body-wave data. At low frequency, the normalized P- or S-wave displacement amplitude spectrum can be approximated by |Ω^(r^,ω)| = 1 − τ2(r^)ω2/2 where r^ specifies a point on the focal sphere. For planar dislocation sources, τ2(r^) is linearly related to statistical measures of source dimension, source duration, and directivity. τ2(r^) can be measured as the curvature of |Ω^(r^,ω)| at ω = 0 or the variance of the pulse Ω^(r^,t). The quantity ωc=2τ−1(r^) is contrasted with the traditional corner frequency ω0, defined as the frequency at the intersection of the low- and high-frequency trends of |Ω^(r^,ω)|. For dislocation models without directivity, ωc(P) ≧ ωc(S) for any r^. A mean corner frequency defined by averaging τ2(r^) over the focal sphere, ω¯c=2<τ2(r^)>−1/2, satisfies ωc(P) > ωc(S) for any dislocation source. This behavior is not shared by ω0. It is shown that ω0 is most sensitive to critical times in the rupture history of the source, whereas ωc is determined by the basic parameters of source extent. Evidence is presented that ωc is the corner frequency measured on actual seismograms. Thus, the commonly observed corner frequency shift (P-wave corner greater than the S-wave corner), now viewed as a shift in ωc is simply a result of spatial finiteness and is expected to be a property of any dislocation source. As a result, the shift cannot be used as a criterion for rejecting particular dislocation models.

Seismic Response of Embankment Dams Based on Recorded Strong-Motion Data in Japan

2019 ◽  
Vol 35 (2) ◽  
pp. 955-976 ◽  
Author(s):  
DongSoon Park ◽  
Tadahiro Kishida
Keyword(s):  
Time Series ◽  
Seismic Response ◽  
Prediction Models ◽  
Strong Motion ◽  
Dynamic Responses ◽  
Design Stage ◽  
Ground Acceleration ◽  
Motion Data ◽  
Embankment Dams ◽  
Strong Motion Database

It is important to investigate strong-motion time series recorded at dams to understand their complex seismic responses. This paper develops a strong-motion database recorded at existing embankment dams and analyzes correlations between dam dynamic responses and ground-motion parameters. The Japan Commission on Large Dams database used here includes 190 recordings at the crests and foundations of 60 dams during 54 earthquakes from 1978 to 2012. Seismic amplifications and fundamental periods from recorded time series were computed and examined by correlation with shaking intensities and dam geometries. The peak ground acceleration (PGA) at the dam crest increases as the PGA at the foundation bedrock increases, but their ratio gradually decreases. The fundamental period broadly increases with the dam height and PGA at the foundation bedrock. The nonlinear dam response becomes more apparent as the PGA at the foundation bedrock becomes >0.2 g. The prediction models of these correlations are proposed for estimating the seismic response of embankment dams, which can inform the preliminary design stage.

Shear‐wave velocity and density estimation from PS-wave AVO analysis: Application to an OBS dataset from the North Sea

Geophysics ◽  
2000 ◽  
Vol 65 (5) ◽  
pp. 1446-1454 ◽  
Author(s):  
Side Jin ◽  
G. Cambois ◽  
C. Vuillermoz
Keyword(s):  
Wave Velocity ◽  
North Sea ◽  
Random Noise ◽  
P Wave ◽  
S Wave ◽  
Data Set ◽  
Avo Analysis ◽  
The North ◽  
Avo Inversion ◽  
The North Sea

S-wave velocity and density information is crucial for hydrocarbon detection, because they help in the discrimination of pore filling fluids. Unfortunately, these two parameters cannot be accurately resolved from conventional P-wave marine data. Recent developments in ocean‐bottom seismic (OBS) technology make it possible to acquire high quality S-wave data in marine environments. The use of (S)-waves for amplitude variation with offset (AVO) analysis can give better estimates of S-wave velocity and density contrasts. Like P-wave AVO, S-wave AVO is sensitive to various types of noise. We investigate numerically and analytically the sensitivity of AVO inversion to random noise and errors in angles of incidence. Synthetic examples show that random noise and angle errors can strongly bias the parameter estimation. The use of singular value decomposition offers a simple stabilization scheme to solve for the elastic parameters. The AVO inversion is applied to an OBS data set from the North Sea. Special prestack processing techniques are required for the success of S-wave AVO inversion. The derived S-wave velocity and density contrasts help in detecting the fluid contacts and delineating the extent of the reservoir sand.

scholarly journals Seismic hazard evaluation

2000 ◽  
Vol 33 (3) ◽  
pp. 371-386 ◽  
Author(s):  
Paul Somerville
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Ground Motions ◽  
Strong Motion ◽  
Earthquake Source ◽  
Hazard Evaluation ◽  
Data Set ◽  
Motion Models ◽  
The Past ◽  
Ground Motion Models

This paper reviews concepts and trends in seismic hazard characterization that have emerged in the past decade, and identifies trends and concepts that are anticipated during the coming decade. New methods have been developed for characterizing potential earthquake sources that use geological and geodetic data in conjunction with historical seismicity data. Scaling relationships among earthquake source parameters have been developed to provide a more detailed representation of the earthquake source for ground motion prediction. Improved empirical ground motion models have been derived from a strong motion data set that has grown markedly over the past decade. However, these empirical models have a large degree of uncertainty because the magnitude - distance - soil category parameterization of these models often oversimplifies reality. This reflects the fact that other conditions that are known to have an important influence on strong ground motions, such as near- fault rupture directivity effects, crustal waveguide effects, and basin response effects, are not treated as parameters of these simple models. Numerical ground motion models based on seismological theory that include these additional effects have been developed and extensively validated against recorded ground motions, and used to estimate the ground motions of past earthquakes and predict the ground motions of future scenario earthquakes. The probabilistic approach to characterizing the ground motion that a given site will experience in the future is very compatible with current trends in earthquake engineering and the development of building codes. Performance based design requires a more comprehensive representation of ground motions than has conventionally been used. Ground motions estimates are needed at multiple annual probability levels, and may need to be specified not only by response spectra but also by suites of strong motion time histories for input into time-domain non-linear analyses of structures.

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