Software to Estimate Earthquake Spectral and Source Parameters

Kumar, Arjun; Kumar, Ashwani; Mittal, Himanshu; Kumar, Ashok; Bhardwaj, Rakhi

doi:10.4236/ijg.2012.35116

Cited by 24 publications

(10 citation statements)

References 16 publications

(17 reference statements)

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“…Therefore, at long periods, the prediction resulted from all models is relatively consistent. This trend was also observed in other studies (for example Kumar, et al [25]).…”

Section: Soil Constitutive Modelssupporting

confidence: 89%

Parametric Study of One-Dimensional Seismic Site Response Analyses Based on Local Soil Condition of Jakarta

Misliniyati

Sahadewa

Hendriyawan

et al. 2019

J. Eng. Technol. Sci.

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Seismic site response analysis is used to estimate the response of soil deposits during seismic loading at any depth of interest and to interpret time histories as well as response spectra. This type of analysis involves many parameters that can affect the character of ground shaking. It is important to know the effect of these parameters in order to perform reliable seismic hazard evaluation at a site. This paper presents the effects of several parameters toward the characteristics of surface response spectra based on the local soil conditions of Jakarta using a one-dimensional (1-D) site response model with total stress approach. A parametric study was performed on two cohesive soil deposit profiles with a different site class, namely medium clay (site S D ) and soft clay (site S E ). The bedrock layers of both profiles were located at a depth of 300 m. In this study, the analytical methods implemented were the equivalent-linear method and the non-linear method. Several different dynamics soil models were also implemented. In addition, variation of property parameters, such as depth of bedrock, shear wave velocity of bedrock, layer thickness, etc., were studied. The results of this study indicate that all of the studied parameters have a significant effect on the response spectra at the ground surface.

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“…Therefore, at long periods, the prediction resulted from all models is relatively consistent. This trend was also observed in other studies (for example Kumar, et al [25]).…”

Section: Soil Constitutive Modelssupporting

confidence: 89%

Parametric Study of One-Dimensional Seismic Site Response Analyses Based on Local Soil Condition of Jakarta

Misliniyati

Sahadewa

Hendriyawan

et al. 2019

J. Eng. Technol. Sci.

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“…The hypocenter parameters (origin time, epicentral distance, latitude, longitude, focal depth, and duration magnitude) are collected from the ENSN bulletins. Meanwhile, the seismic source spectral parameters are estimated using the EQK_SRC_PARA software 31 . The used parameters are the duration magnitude (Md), P-wave spectrum corner frequency (Pcf), S-wave corner frequency (Scf), and the ratio (Rcf) of Pcf to Scf.…”

Section: Data Setmentioning

confidence: 99%

“…For any new event of an unknown source, the three parameters are estimated using the EQK_SRC_PARA software 31 as indicated earlier.…”

Section: Stage 1 (Ann)mentioning

confidence: 99%

Discrimination between Small Earthquakes and Local Quarry Blasts Using Committee Machine

Lethy

Othman

Gabry

et al. 2021

Preprint

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A combination of multiple discrimination artificial neural networks using different seismic source parameters is suggested using a committee machine. In this work, a committee machine was used to combine supervised and unsupervised artificial neural networks to discriminate between earthquakes and quarry blasts using data from the Egyptian National Seismological Network (ENSN). The unsupervised network is used as a measure of accuracy for the results of the supervised neural network. The unsupervised Self-Organized Map (SOM) and the k-means clustering algorithms are used to estimate support and confidence measures for the results. Meanwhile, the supervised neural network is used to discriminate between earthquakes and explosions. The artificial neural networks are trained using different input parameters which are the P wave spectrum corner frequency (PcF), S wave corner frequency (ScF), and the ratio (Rcf) of PcF to Scf. The combined approach succeeds to discriminate between earthquakes and quarry blasts in Northern Egypt. The method provides the results with a measure of confidence which eliminates false discrimination. The current paper represents an idea to implement artificial intelligence to assist experts in decision-making situations. The committee machine could identify the nature of a particular event, using the aid of several discrimination methods. The proposed committee machine could combine the results of several algorithms and expert opinions to form one single output with a confidence measure.

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“…To remove the regional absorption effect, assessment of acceleration reduction is used (Kurtulmuş and Akyol, 2013). In the ground displacement spectrum, as a result of calculating the low frequency level, corner frequency and slope, related empirical equations (Kumar et al, 2012) are used to calculate the source radius, seismic moment and mean stress drop. For the 06 February 2017 earthquake Mw=5.5, Mo= 2.1E17 Nm and mean ∆σ= 12 Mpa were calculated.…”

Section: Seismic Source Analysismentioning

confidence: 99%

Preliminary Observations and Assessment of Çanakkale-Ayvacık Earthquake Activity

Bekler

Demirci

2018

Çanakkale Onsekiz Mart Üniversitesi Fen Bilimleri Enstitüsü Dergisi

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A project was begun to monitor earthquake activity at the southwest branch of the Biga Peninsula in Ayvacık and close surroundings beginning on 14 January 2017 with Mw=4.6 and continuing through 6 February 2017 with Mw=5.5 (Mw=5.5 Kandilli Observatory and Earthquake Research Institute -KOERI -, Mw=5.3 AFAD, Mw=5.4 ÇOMÜ). The region has active seismicity and includes portions of the significant tectonic elements of the northwest Aegean region. Due to the continuation of earthquake activity, in addition to permanent stations linked to the national networks (KOERI and AFAD) in the region 10 continuousform recording 3-component temporary stations were set up with the aim of observation for at least 1 year. The distances between these stations varied from 6 to 12 km. In addition to the intensity and continuity of microearthquake activity in the region, and the inclusion of geothermal fields in the region, the necessity to investigate the seismotectonic character of the region in detail came to the agenda. Together with permanent stations belonging to national observatories in the study area, the station density was insufficient to reveal these details. As a result, data from both national network and temporary stations will contribute to understanding the tectonic character of the region. When temporary stations at close proximity to the main shock and epicenter distribution are compared with the national network primary results indicate there were significant improvements in identifying microearthquakes especially and in determining their locations. Additionally, and in source mechanism solutions belonging to earthquake data with moderate magnitude, faulting with a dominantly NW-SE oriented normal offset component was observed. This study aims to reveal the time and spatial distribution, frequency content and source mechanisms for earthquakes occurring in the southwest of the Biga Peninsula near Ayvacık and surroundings, in addition to determining a detailed velocity model with local tomography.

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Software to Estimate Earthquake Spectral and Source Parameters

Cited by 24 publications

References 16 publications

Parametric Study of One-Dimensional Seismic Site Response Analyses Based on Local Soil Condition of Jakarta

Parametric Study of One-Dimensional Seismic Site Response Analyses Based on Local Soil Condition of Jakarta

Discrimination between Small Earthquakes and Local Quarry Blasts Using Committee Machine

Preliminary Observations and Assessment of Çanakkale-Ayvacık Earthquake Activity

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