Regional modification of acceleration attenuation functions

1981 ◽  
Vol 71 (4) ◽  
pp. 1309-1321
Author(s):  
James Battis
Keyword(s):  
Wave Attenuation ◽  
Strong Motion ◽  
Ground Acceleration ◽  
Strong Motion Data ◽  
Motion Data ◽  
Ground Motion Attenuation ◽  
Instrumental Observations ◽  
Epicentral Intensity ◽  
Felt Area ◽  
Event Magnitude

abstract Strong ground motion attenuation functions developed on the basis of data from one physiographic region do not generally apply to other regions due to both differences in source characteristics and seismic wave attenuation. At the same time, many regions with known seismic hazard lack sufficient strong motion data to develop regionally unique attenuation functions. A method is proposed for the estimation of peak ground acceleration attenuation functions for these regions. The technique makes use of regional variations in relationships between event magnitude and epicentral intensity and event magnitude and radius of the felt area to correlate peak ground accelerations from a region which has empirical strong motion data to one lacking this data. The necessary relationships to make the modifications require only limited instrumental observations. The method is an improvement over previously suggested schemes in that the fundamental assumptions are more restricted than those previously used.

scholarly journals Strong motion data centre

1971 ◽  
Vol 4 (1) ◽  
pp. 15-30
Author(s):  
D. Denham ◽  
G. R. Small
Keyword(s):  
Volcanic Ash ◽  
Strong Motion ◽  
Mineral Resources ◽  
Australian Bureau ◽  
Ground Acceleration ◽  
Strong Motion Data ◽  
Motion Data ◽  
Data Centre ◽  
Unconsolidated Material ◽  
Storage Distribution

A Strong Motion Data Centre, for the collection, storage, distribution and preliminary analysis of accelerograms from the Australian and New Guinean regions, has recently been established at Canberra by the Australian Bureau of Mineral Resources. The work undertaken at the Centre is described and examples of the processing facilities available are given. Extensive use is made of computers in the analysis of the accelerograms and the plotting of the results. By December 1970 thirteen accelerographs had been obtained, by several institutions, for installation in the Australian and New Guinea regions and 24 accelerograms had been received at the Centre for analysis. The instruments located on unconsolidated material at Lae, Yonki and Panguna are currently producing about 5 accelerograms per year and the maximum ground acceleration recorded so far, of 0.12g, was obtained at Panguna, where the accelerograph is located on recent unconsolidated volcanic ash.

Ground motion models for shallow crustal and deep earthquakes in Hawaii and analyses of the 2018 M 6.9 Kalapana sequence

2021 ◽  
pp. 875529302110445
Author(s):  
Ivan Wong ◽  
Robert Darragh ◽  
Sarah Smith ◽  
Qimin Wu ◽  
Walter Silva ◽  
...  
Keyword(s):  
Ground Motion ◽  
Epicentral Distance ◽  
Strong Motion ◽  
Earthquake Hazards ◽  
Ground Acceleration ◽  
Strong Motion Data ◽  
Ground Shaking ◽  
Motion Data ◽  
Crustal Earthquake ◽  
Deep Earthquakes

The damaging 4 May 2018 M 6.9 Kalapana earthquake and its aftershocks have provided the largest suite of strong motion records ever produced for an earthquake sequence in Hawaii exceeding the number of records obtained in the deep 2006 M 6.7 Kiholo Bay earthquake. These records provided the best opportunity to understand the processes of strong ground shaking in Hawaii from shallow crustal (< 20 km) earthquakes. There were four foreshocks and more than 100 aftershocks of M 4.0 and greater recorded by the seismic stations. The mainshock produced only a modest horizontal peak ground acceleration (PGA) of 0.24 g at an epicentral distance of 21.5 km. In this study, we evaluated the 2018 strong motion data as well as previously recorded shallow crustal earthquakes on the Big Island. There are still insufficient strong motion data to develop an empirical ground motion model (GMM) and so we developed a GMM using the stochastic numerical modeling approach similar to what we had done for deep Hawaiian (>20 km) earthquakes. To provide inputs into the stochastic model, we performed an inversion to estimate kappa, stress drops, Ro, and Q(f) using the shallow crustal earthquake database. The GMM is valid from M 4.0 to 8.0 and at Joyner–Boore (RJB) distances up to 400 km. Models were developed for eight VS30 (time-averaged shear-wave velocity in the top 30 m) values corresponding to the National Earthquake Hazards Reduction Program (NEHRP) site bins: A (1500 m/s), B (1080 m/s), B/C (760 m/s), C (530 m/s), C/D (365 m/s), D (260 m/s), D/E (185 m/s), and E (150 m/s). The GMM is for PGA, peak horizontal ground velocity (PGV), and 5%-damped pseudo-spectral acceleration (SA) at 26 periods from 0.01 to 10 s. In addition, we updated our GMM for deep earthquakes (>20 km) to include the same NEHRP site bins using the same approach for the crustal earthquake GMM.

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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