Characterization of shear wave attenuation and site effects in the Garhwal Himalaya, India from inversion of strong motion records

2021 ◽  
Vol 130 (4) ◽  
Author(s):  
Parveen Kumar ◽  
Monika ◽  
Sandeep ◽  
Sushil Kumar ◽  
Richa Kumari ◽  
...  
2011 ◽  
Vol 101 (5) ◽  
pp. 2252-2269 ◽  
Author(s):  
I. G. Wong ◽  
K. H. Stokoe ◽  
B. R. Cox ◽  
J. Yuan ◽  
K. L. Knudsen ◽  
...  

2010 ◽  
Vol 26 (2) ◽  
pp. 499-524 ◽  
Author(s):  
Adrian Rodriguez-Marek ◽  
James A. Bay ◽  
Kwangsoo Park ◽  
Gonzalo A. Montalva ◽  
Adel Cortez-Flores ◽  
...  

The Mw 8.4 23 June 2001 Southern Peru earthquake generated intense ground motions in a large region encompassing southern Peru and northern Chile. The earthquake was recorded by seven strong motion stations with peak ground accelerations ranging from 0.04 g to 0.34 g for site-to-fault distances ranging from about 70 km to 220 km. At this time, there are no other strong motion records for an earthquake of this magnitude. Hence, the strong motion data set from this earthquake is unique and of particular interest to engineers dealing with seismic design in subduction regions. This paper presents an engineering analysis of the strong motion records. Shear-wave velocity profiles were measured using Spectral Analysis of Surface Waves methods at four stations. Measured shear-wave velocities are high, indicating that all sites classify as stiff soil sites (Site C) according to the International Building Code classification scheme. The strong motion set is characterized by strong high frequency content at large distances from the fault. Site response contributed at least in part to the observed high frequency content in the ground motions. In general, current attenuation relationships for spectral acceleration underpredicted the observed ground motions.


2021 ◽  
Author(s):  
Mona Izadi ◽  
Shinichi Matsushima

Abstract It is known that coda of strong motion records are products of numerous scatterings of body and surface waves within the subsurface soil structure. Several studies have successfully simulated coda wave envelopes by modelling the energy decay. However, due to limitations of quantifying soil heterogeneities, deterministic simulation of scattered wavefields is much more challenging. Therefore, the reverse problem of estimating non statistical properties of subsurface structure from coda waves remains a theoretical potential. On the other hand, machine learning techniques have proven useful in dealing with problems of similar nature, where a theoretical solution is imaginable yet hard to achieve due to a great number of unknown variables. This study utilizes artificial neural networks to propose a new approach of evaluating site effects from coda waves, with the future prospect of obtaining the similar results from microtremor records. A Long Short-Term Memory recurrent neural network is designed using Tensorflow 2 library in Python language. The study utilizes a strong motion dataset consisting of about 60000 3-component records as well as borehole data at 464 stations of Kiban-Kyoshin Network across Japan. The prediction input is coda wave timeseries of strong motion records, defined based on a parametric energy criterion, and all 3 seismograph components EW, NS and UD are used as parallel sequential features. In the first step, the prediction target is a vector of 3 site effect proxies namely, time-averaged shear-wave velocities for the upper 30-m depth Vs30 and the upper 10-m depth Vs10 and predominant frequency f0. In this step, different model parameter combinations are tested to ensure the basic model’s ability in extracting site-specific information from the input coda waves. One of the combinations is then used in the second step, in which the prediction target is surface to downhole ratio of Fourier Amplitude Spectra. For each of the 3 components EW, NS and UD, 100 identical networks are trained to each predict the desired ratio at a certain target frequency. Accuracy of test sample predictions confirms applicability of the proposed approach as well as its potential for future works on microtremor timeseries instead of coda waves.


1998 ◽  
Vol 14 (1) ◽  
pp. 75-93 ◽  
Author(s):  
Francisco J. Chávez-García ◽  
Julio Cuenca

The region around Acapulco, on the Pacific coast of Mexico, is subjected to large seismic risk. This paper presents a contribution to improve microzonation of this region. We investigated site effects using three basic sources of data: strong-motion records from all of the instruments that have operated within the area; weak-motion records obtained from the installation and operation of a temporal, digital, seismograph network; and measurements of microtremors at 35 sites. We compared and evaluated different techniques of data analysis. We show that very coherent results are obtained from different kinds of measurement, and that microtremor records are very useful to interpolate sparse earthquake data. We propose two maps that reflect the fundamental characteristics of site effects in the area: dominant period and maximum relative amplification. These maps may be used to improve current microzonation of Acapulco.


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