A multiple time window rupture model for the 1999 Chi-Chi earthquake from a combined inversion of teleseismic, surface wave, strong motion, and GPS data

2004 ◽  
Vol 109 (B8) ◽  
Author(s):  
H. K. Thio ◽  
R. W. Graves ◽  
P. G. Somerville ◽  
T. Sato ◽  
T. Ishii
Keyword(s):  
Surface Wave ◽  
Time Window ◽  
Strong Motion ◽  
Gps Data ◽  
Multiple Time ◽  
Rupture Model

scholarly journals RETRACTED ARTICLE: Estimation of the source process and forward simulation of long-period ground motion of the 2018 Hokkaido Eastern Iburi, Japan, earthquake

2019 ◽  
Vol 71 (1) ◽  
Author(s):  
Hisahiko Kubo ◽  
Asako Iwaki ◽  
Wataru Suzuki ◽  
Shin Aoi ◽  
Haruko Sekiguchi
Keyword(s):  
Ground Motion ◽  
Velocity Structure ◽  
Time Window ◽  
Waveform Inversion ◽  
Strong Motion ◽  
Source Model ◽  
Multiple Time ◽  
Velocity Models ◽  
Long Period ◽  
Slip Area

Abstract In this study, we investigate the source rupture process of the 2018 Hokkaido Eastern Iburi earthquake in Japan (MJMA 6.7) and how the ground motion can be reproduced using available source and velocity models. First, we conduct a multiple-time-window kinematic waveform inversion using strong-motion waveforms, which indicates that a large-slip area located at a depth of 25–30 km in the up-dip direction from the hypocenter was caused by a rupture propagating upward 6–12 s after its initiation. Moreover, the high-seismicity area of aftershocks did not overlap with the large-slip area. Subsequently, using the obtained source model and a three-dimensional velocity structure model, we conduct a forward long-period (< 0.5 Hz) ground-motion simulation. The simulation was able to reproduce the overall ground-motion characteristics in the sedimentary layers of the Ishikari Lowland.

3-D joint geodetic and strong-motion finite fault inversion of the 2008 May 12, Wenchuan, China Earthquake

2020 ◽  
Vol 222 (2) ◽  
pp. 1390-1404
Author(s):  
Leonardo Ramirez-Guzman ◽  
Stephen Hartzell
Keyword(s):  
Time Window ◽  
Joint Inversion ◽  
Strong Motion ◽  
Multiple Time ◽  
Source Inversion ◽  
Geodetic Inversion ◽  
Finite Fault Inversion ◽  
Finite Fault ◽  
China Earthquake ◽  
The Moment

SUMMARY We present a source inversion of the 2008 Wenchuan, China earthquake, using strong-motion waveforms and geodetic offsets together with 3-D synthetic ground motions. We applied the linear multiple time window technique considering geodetic and dynamic Green's functions computed with the finite-element method and the reciprocity and Strain Green's Tensor formalism. All ground motion estimates, valid up to 1 Hz, accounted for 3-D effects, including the topography and the geometry of the Beichuan and Pengguan faults. Our joint inversion has a higher moment (M0) than a purely geodetic inversion and the slip distribution presents differences when compared to 1-D model source inversions. The moment is estimated to be M0 = 1.2 × 1021 N·m, slightly larger than other works. Our results show that considering a complex 3-D structure reduces the size of large areas of 10 m slip or greater by distributing it in wider zones, with reduced slips, in the central portion of the Beichuan and the Pengguan faults. Finally, we compare our source with a relocated aftershock catalogue and conclude that the 4–5 m slip contours approximately bound the absence or presence of aftershocks.

Slip history of the 1994 Sanriku-Haruka-Oki, Japan, earthquake deduced from strong-motion data

1997 ◽  
Vol 87 (4) ◽  
pp. 918-931 ◽  
Author(s):  
Wataru Nakayama ◽  
Minoru Takeo
Keyword(s):  
Seismic Waves ◽  
Time Window ◽  
Strong Motion ◽  
Rupture Process ◽  
Multiple Time ◽  
Strong Motion Data ◽  
Motion Data ◽  
The Third ◽  
Slip History ◽  
Double Couple

Abstract We analyzed the seismic waves of the 1994 Sanriku-Haruka-Oki earthquake (Mw = 7.7), which occurred in the aftershock area of the 1968 Tokachi-Oki earthquake (Mw = 8.2). Applying a multiple-time window inversion scheme to near-source strong-motion data, we obtained a detailed spatiotemporal rupture process and compared it with that of the Tokachi-Oki earthquake. The fault geometry is constructed based on the aftershock distribution. The obtained rupture model is consistent with the CMT solution even for a non-double-couple component. The total seismic moment is 4.0 × 1020 N-m. Large slips are concentrated in three asperities: the first asperity centers about 40 km south and 50 km west from the hypocenter with a maximum slip of 4.4 m, the second one centers about 60 km west from the hypocenter with a maximum slip of 2.2 m, and the third one lies about 110 km west from the hypocenter with a maximum slip of 2.6 m. The obtained moment rate and the duration on the first and second asperities are lower and much longer than those on the third asperity, respectively. The first asperity does not overlap with an area of large slip during the Tokachi-Oki earthquake, but the second or third seem to overlap with or be adjacent to the asperity of the Tokachi-Oki earthquake. Our inversion result also shows an abrupt change of the rupture velocity (from 1.8 to 3.0 km/sec) at the central part of the fault plane. A difference of the seismic coupling between the oceanic and the continental lithospheres at the trenchward side and at the landward side of the 143° E meridian seems to affect the rupture process of this earthquake.

scholarly journals Rupture process of the 1987 Superstition Hills earthquake from the inversion of strong-motion data

1990 ◽  
Vol 80 (5) ◽  
pp. 1079-1098 ◽  
Author(s):  
David J. Wald ◽  
Donald V. Helmberger ◽  
Stephen H. Hartzell
Keyword(s):  
Small Area ◽  
Strong Motion ◽  
Rupture Process ◽  
Imperial Valley ◽  
Strong Motion Records ◽  
Motion Data ◽  
Single Asperity ◽  
The Third ◽  
Rupture Model ◽  
Stress Drops

Abstract A pair of significant earthquakes occurred on conjugate faults in the western Imperial Valley involving the through-going Superstition Hills fault and the Elmore Ranch cross fault. The first event was located on the Elmore Ranch fault, Ms = 6.2, and the larger event on the Superstition Hills fault, Ms = 6.6. The latter event is seen as a doublet teleseismically with the amplitudes in the ratio of 1:2 and delayed by about 8 sec. This 8-sec delay is also seen in about a dozen strong-motion records. These strong-motion records are used in a constrained least-squares inversion scheme to determine the distribution of slip on a 2-D fault. Upon closer examination, the first of the doublets was found to be itself complex requiring two episodes of slip. Thus, the rupture model was allowed to have three separate subevents, treated as separate ruptures, with independent locations and start times. The best fits were obtained when all three events initiated at the northwestern end of the fault near the intersection of the cross-fault. Their respective delays are 2.1 and 8.6 sec relative to the first subevent, and their moments are 0.4, 0.9, and 3.5 × 1025 dyne-cm, which is about half of that seen teleseismically. This slip distribution suggests multi-rupturing of a single asperity with stress drops of 60, 200, and 15 bars, respectively. The first two subevents were confined to a small area around the epicenter while the third propagated 18 km southwestward, compatible with the teleseismic and afterslip observations.

scholarly journals Multi-UAV Reconnaissance Task Assignment for Heterogeneous Targets Based on Modified Symbiotic Organisms Search Algorithm

Sensors ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 734 ◽  
Author(s):  
Hao-Xiang Chen ◽  
Ying Nan ◽  
Yi Yang
Keyword(s):  
Assignment Problem ◽  
Time Window ◽  
Search Algorithm ◽  
Task Assignment ◽  
Multiple Time ◽  
Nsga Ii ◽  
Symbiotic Organisms Search ◽  
Simulation Results ◽  
Symbiotic Organisms ◽  
Task Assignment Problem

This paper considers a reconnaissance task assignment problem for multiple unmanned aerial vehicles (UAVs) with different sensor capacities. A modified Multi-Objective Symbiotic Organisms Search algorithm (MOSOS) is adopted to optimize UAVs’ task sequence. A time-window based task model is built for heterogeneous targets. Then, the basic task assignment problem is formulated as a Multiple Time-Window based Dubins Travelling Salesmen Problem (MTWDTSP). Double-chain encoding rules and several criteria are established for the task assignment problem under logical and physical constraints. Pareto dominance determination and global adaptive scaling factors is introduced to improve the performance of original MOSOS. Numerical simulation and Monte-Carlo simulation results for the task assignment problem are also presented in this paper, whereas comparisons with non-dominated sorting genetic algorithm (NSGA-II) and original MOSOS are made to verify the superiority of the proposed method. The simulation results demonstrate that modified SOS outperforms the original MOSOS and NSGA-II in terms of optimality and efficiency of the assignment results in MTWDTSP.

scholarly journals Combining strong-motion, InSAR and GPS data to refine the fault geometry and source kinematics of the 2011, Mw 6.2, Christchurch earthquake (New Zealand)

2013 ◽  
Vol 194 (3) ◽  
pp. 1760-1777 ◽  
Author(s):  
Eugenio Maria Toraldo Serra ◽  
Bertrand Delouis ◽  
Antonio Emolo ◽  
Aldo Zollo
Keyword(s):  
New Zealand ◽  
Strong Motion ◽  
Gps Data ◽  
Fault Geometry

Effect of inaccurate specification of time-correlated model error in an Ensemble Smoother

2020 ◽  
Author(s):  
Haonan Ren ◽  
Peter Jan Van Leeuwen ◽  
Javier Amezcua
Keyword(s):  
Data Assimilation ◽  
Time Scale ◽  
Correlation Time ◽  
Time Window ◽  
Model Error ◽  
Multiple Time ◽  
Model Errors ◽  
Time Step ◽  
Single Observation ◽  
Kalman Smoother

&lt;p&gt;Data assimilation has been often performed under the perfect model assumption known as the strong-constraint setting. There is an increasing number of researches accounting for the model errors, the weak-constrain setting, but often with different degrees of approximation or simplification without knowing their impact on the data assimilation results. We investigate what effect inaccurate model errors, in particular, the an inaccurate time correlation, can have on data assimilation results, with a Kalman Smoother and the Ensemble Kalman Smoother.&lt;br&gt;We choose a linear auto-regressive model for the experiment. We assume the true state of the system has the correct and fixed correlation time-scale&amp;#160;&amp;#969;&lt;sub&gt;r&lt;/sub&gt; in the model errors, and the prior or the background generated by the model contains the model error with the fixed, guessed time-scale &amp;#969;&lt;sub&gt;g&lt;/sub&gt; which differs from the correct one and is also used in the data assimilation process. There are 10 variables in the system and we separate the simulation period into multiple time-windows. And we use a fairly large ensemble size (up to 200 ensemble members) to improve the accuracy of the data assimilation results. In order to evaluate the performance of the EnKS with auto-correlated model errors, we calculate the ratio of root-mean-square error over the spread of all ensemble members.&lt;br&gt;The results with a single observation at the end of the simulation time-window show that, using an underestimated correlation time-scale leads to overestimated spread of the ensemble, and with an overestimated time-scale, the results show underestimation in the ensemble spread. However, with very dense observation frequency, observing every time-step for instance, the results are completely opposite to the results with a single observation. In order to understand the results, we derive the expression for the true posterior state covariance and the posterior covariance using the incorrect decorrelation time-scale. We do this for a Kalman Smoother to avoid the sampling uncertainties. The results are richer than expected and highly dependent on the observation frequency. From the analytical solution of the analysis, we find that the RMSE is a function of both &amp;#969;&lt;sub&gt;r&lt;/sub&gt;&lt;sub&gt;&amp;#160;&lt;/sub&gt;and &amp;#969;&lt;sub&gt;g&lt;/sub&gt;, and the spread or the variance only depends on &amp;#969;&lt;sub&gt;g&lt;/sub&gt;. We also find that the analyzed variance is not always a monotonically increasing function of &amp;#969;&lt;sub&gt;g&lt;/sub&gt;, and it also depends on the observation frequency. In general, the results show the effect of the correlated model error and the incorrect correlation time-scale on data assimilation result, which is also affected by the observation frequency.&lt;/p&gt;

Classification of Main Shocks and Aftershocks in the NGA-West2 Database

2014 ◽  
Vol 30 (3) ◽  
pp. 1257-1267 ◽  
Author(s):  
Kathryn E. Wooddell ◽  
Norman A. Abrahamson
Keyword(s):  
Time Window ◽  
Strong Motion ◽  
Data Sets ◽  
Horizontal Distance ◽  
Strong Motion Data ◽  
Motion Data ◽  
Rupture Plane ◽  
Main Shocks ◽  
Short Period ◽  
Surface Projection

Previous studies have found a systematic difference between short-period ground motions from aftershocks and main shocks, but have not used a consistent methodology for classifying earthquakes in strong motion data sets. A method for unambiguously classifying earthquakes in strong motion data sets is developed. The classification is based on the Gardner and Knopoff time window, but with a distance window based on a new distance metric, CRJB, defined as the shortest horizontal distance between the centroid of the surface projection of the potential aftershock rupture plane and the surface projection of the main shock rupture plane. Class 2 earthquakes are earthquakes that have a CRJB distance less than a selected limit and within a time window appropriate for aftershocks. All other earthquakes are classified as Class 1. For maximum CRJB of 0 km and 40 km, 11% and 36% of the earthquakes in the NGA-West2 database are Class 2 events, respectively.

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