scholarly journals The Influence of Weighted Regression Analysis and Diversity of Strong Motion Data on the Distance-Dependent Variance of Peak Ground Acceleration and Peak Ground Velocity

2014 ◽  
Vol 14 (2) ◽  
pp. 2_185-2_189
Author(s):  
Yasuo UCHIYAMA
Keyword(s):  
Regression Analysis ◽  
Peak Ground Acceleration ◽  
Strong Motion ◽  
Peak Ground Velocity ◽  
Weighted Regression ◽  
Ground Acceleration ◽  
Strong Motion Data ◽  
Motion Data ◽  
Weighted Regression Analysis

Strong-Motion Data from Structural Response Recorders in Indian Earthquakes

2012 ◽  
Vol 28 (1) ◽  
pp. 77-103 ◽  
Author(s):  
Sudhir K. Jain ◽  
A. D. Roshan ◽  
Siddharth Yadav ◽  
Sonam Srivastava ◽  
Prabir C. Basu
Keyword(s):  
Peak Ground Acceleration ◽  
Structural Response ◽  
Time History ◽  
Strong Motion ◽  
Ground Acceleration ◽  
Motion Data ◽  
The Past ◽  
Simple Instrument ◽  
Low Costs ◽  
The 1960S

In the 1960s several hundred structural response recorders (SRR) were installed all over India. An SRR is a simple instrument consisting of six seismoscopes that provide “maximum response” during an earthquake, without providing the time history. In the past earthquakes, these SRRs have provided several hundred records but they have not been effectively utilized for hazard studies because the measurements from these instruments are considered crude. This paper compares the data obtained from SRRs with that from more modern strong-motion accelerographs (SMAs) for four earthquakes in India. It is shown through statistical analysis that the response obtained from the SRRs is comparable to that from the SMAs. A method has been presented for estimating peak ground acceleration (PGA) from SRR data. Thus, it is shown that SRRs can provide a substantial amount of PGA data for attenuation studies. Many countries may find SRRs useful because of the low costs associated with their manufacture and maintenance.

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.

A Seismic Intensity Survey of the 16 April 2016 Mw 7.8 Pedernales, Ecuador, Earthquake: A Comparison with Strong-Motion Data and Teleseismic Backprojection

2021 ◽  
Author(s):  
Ellen M. Smith ◽  
Walter D. Mooney
Keyword(s):  
Emergency Response ◽  
Strong Motion ◽  
Seismic Intensity ◽  
Peak Ground Velocity ◽  
Ground Acceleration ◽  
Motion Data ◽  
Contour Maps ◽  
Crustal Earthquakes ◽  
Maximum Value ◽  
Large Earthquakes

Abstract We conducted a seismic intensity survey in Ecuador, following the 16 April 2016 Mw 7.8 Pedernales earthquake, to document the level of damage caused by the earthquake. Our modified Mercalli intensities (MMIs) reach a maximum value of VIII along the coast, where single, two, and multistory masonry and concrete designed buildings partially or completely collapsed. The contours of our MMI maps are similar in shape to the contour maps of peak ground acceleration (PGA) and peak ground velocity (PGV). A comparison of our seismic intensities with the recorded PGA and PGV values reveals that our MMI values are lower than predicted by ground-motion intensity conversion equations that are based on shallow crustal earthquakes. The image of the earthquake rupture obtained using teleseismic backprojection at 0.5–2.0 Hz is coincident with the region of maximum MMI, PGA, and PGV values, Thus, rapid calculation of backprojection may be a useful tool for guiding the deployment of emergency response teams following large earthquakes. The most severe damage observed was, primarily, due to a combination of poorly constructed buildings and site conditions.

New Ground Motion to Intensity Conversion Equations (GMICEs) for New Zealand

2020 ◽  
Vol 92 (1) ◽  
pp. 448-459 ◽  
Author(s):  
Jose M. Moratalla ◽  
Tatiana Goded ◽  
David A. Rhoades ◽  
Silvia Canessa ◽  
Matthew C. Gerstenberger
Keyword(s):  
New Zealand ◽  
Ground Motion ◽  
Strong Motion ◽  
Peak Ground Velocity ◽  
Least Squares Regression ◽  
Data Types ◽  
Ground Acceleration ◽  
Hypocentral Distance ◽  
Motion Data ◽  
Recent Earthquakes

Abstract Macroseismic intensities play a key role in the engineering, seismological, and loss modeling communities. However, at present, there is an increasing demand for instrumental data-based loss estimations that require statistical relationships between intensities and strong-motion data. In New Zealand, there was an urgent need to update the ground motion to intensity conversion equation (GMICE) from 2007, developed prior to a large number of recent earthquakes including the 2010–2011 Canterbury and 2016 Kaikōura earthquake sequences. Two main factors now provide us with the opportunity to update New Zealand’s GMICE: (1) recent publication of New Zealand’s Strong-Motion Database, corresponding to 276 New Zealand earthquakes with magnitudes 3.5–7.8 and 4–185 km depths; and (2) recent generation of a community intensity database from GeoNet’s “Felt Classic” (2004–2016) and “Felt Detailed” (2016–2019) questionnaires, corresponding to around 930,000 individual reports. Ground-motion data types analyzed are peak ground velocity (PGV) and peak ground acceleration (PGA). The intensity database contains 67,572 felt reports from 917 earthquakes, with magnitudes 3.5–8.1, and 1797 recordings from 247 strong-motion stations (SMSs), with hypocentral distances of 5–345 km. Different regression analyses were tested, and the bilinear regression of binned mean strong-motion recordings for 0.5 modified Mercalli intensity bins was selected as the most appropriate. Total least squares regression was chosen for reversibility in the conversions. PGV provided the best-fitting results, with lower standard deviations. The influence of hypocentral distance, earthquake magnitude, and the site effects of local geology, represented by the mean shear-wave velocity in the first 30 m depth, on the residuals was also explored. A regional correction factor for New Zealand, suitable for adjustment of global relationships, has also been estimated.

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.

Magnitude-dependent variance of peak ground acceleration

1995 ◽  
Vol 85 (4) ◽  
pp. 1161-1176
Author(s):  
R. R. Youngs ◽  
N. Abrahamson ◽  
F. I. Makdisi ◽  
K. Sadigh
Keyword(s):  
Standard Error ◽  
Peak Ground Acceleration ◽  
Strong Motion ◽  
Earthquake Magnitude ◽  
Peak Acceleration ◽  
Ground Acceleration ◽  
Data Set ◽  
Motion Data ◽  
Time Period ◽  
Vertical Accelerations

Abstract We examine the variability of peak horizontal and vertical accelerations of the large California strong-motion data set for the time period 1957 to 1991 and find a statistically significant dependence of the standard error on earthquake magnitude. Specifically, the standard error decreases with increasing magnitude. The analysis was conducted using a rigorous methodology that examines both earthquake to earthquake (inter-event) variability and within earthquake (intra-event) variability. The magnitude dependence is stronger for inter-event variability than intra-event variability, and stronger for horizontal peak acceleration than for vertical peak acceleration. The data from the recent Landers, Big Bear, and Northridge earthquakes are consistent with these results.

Methods for regression analysis of strong-motion data

1994 ◽  
Vol 84 (3) ◽  
pp. 955-956
Author(s):  
William B. Joyner ◽  
David M. Boore
Keyword(s):  
Regression Analysis ◽  
Strong Motion ◽  
Strong Motion Data ◽  
Motion Data

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.

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