Determination of Design Ground Motion For Critical Engineering Structures Based on Probabilistic Seismic Hazard Analysis

2006 ◽  
Author(s):  
Guoxin Wang ◽  
Zhen Zhao
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Engineering Structures

Ranking of Ground-Motion Models (GMMs) for Use in Probabilistic Seismic Hazard Analysis for Iran Based on an Independent Data Set

2020 ◽  
Author(s):  
Zoya Farajpour ◽  
Milad Kowsari ◽  
Shahram Pezeshk ◽  
Benedikt Halldorsson
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Selection Process ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Data Set ◽  
Motion Models ◽  
Ground Motion Models

ABSTRACT We apply three data-driven selection methods, log-likelihood (LLH), Euclidean distance-based ranking (EDR), and deviance information criterion (DIC), to objectively evaluate the predictive capability of 10 ground-motion models (GMMs) developed from Iranian and worldwide data sets against a new and independent Iranian strong-motion data set. The data set includes, for example, the 12 November 2017 Mw 7.3 Ezgaleh earthquake and the 25 November 2018 Mw 6.3 Sarpol-e Zahab earthquake and includes a total of 201 records from 29 recent events with moment magnitudes 4.5≤Mw≤7.3 with distances up to 275 km. The results of this study show that the prior sigma of the GMMs acts as the key measure used by the LLH and EDR methods in the ranking against the data set. In some cases, this leads to the resulting model bias being ignored. In contrast, the DIC method is free from such ambiguity as it uses the posterior sigma as the basis for the ranking. Thus, the DIC method offers a clear advantage of partially removing the ergodic assumption from the GMM selection process and allows a more objective representation of the expected ground motion at a specific site when the ground-motion recordings are homogeneously distributed in terms of magnitudes and distances. The ranking results thus show that the local models that were exclusively developed from Iranian strong motions perform better than GMMs from other regions for use in probabilistic seismic hazard analysis in Iran. Among the Next Generation Attenuation-West2 models, the GMMs by Boore et al. (2014) and Abrahamson et al. (2014) perform better. The GMMs proposed by Darzi et al. (2019) and Farajpour et al. (2019) fit the recorded data well at short periods (peak ground acceleration and pseudoacceleration spectra at T=0.2  s). However, at long periods, the models developed by Zafarani et al. (2018), Sedaghati and Pezeshk (2017), and Kale et al. (2015) are preferable.

scholarly journals ANALISIS PROBABILISTIK BAHAYA GEMPA PADA BENDUNGAN WADASLINTANG

2018 ◽  
Vol 6 (4) ◽  
Author(s):  
Rahma Kusuma Dewi ◽  
Yusep Muslih Purwana ◽  
Raden Harya Dananjaya
Keyword(s):  
Seismic Hazard ◽  
Ground Motion ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard

<p>Indonesia merupakan salah satu negara dengan dengan tingkat intensitas kegempaan yang cukup tinggi, terlihat dari lokasinya yang berdekatan dengan sumber-sumber gempa diantaranya, zona subduksi, sesar (fault) yang aktif, dan cinicin api pasifik (gunung berapi) yang tersebar di sepanjang negara kepulauan ini. Diantara beberapa pulau di Indonesia, Pulau Jawa menjadi salah satu pulau dengan aktivitas seismik yang tinggi. Pulau dengan jumlah penduduk paling banyak, sebagai pusat pemerintahan dan kegiatan industri menjadikan Jawa mempunyai tingkat resiko kerusakan bangunan dan infrastruktur yang cukup tinggi. Salah satu bangunan yang mempunyai tingkat resiko tinggi adalah bendungan urugan. Penelitian ini akan mengevaluasi bahaya gempa pada salah satu bendungan besar Indonesia yaitu Bendungan Wadaslintang. Bendungan ini terletak di perbatasan 3 kabupaten besar yaitu Kabupaten Kebumen, Purworejo dan Wonosobo. Bendungan ini dibangun pada tahun 1982 sampai 1987, dengan tinggi 116 m. Mengingat usia bendungan yang mencapai 31 tahun serta potensi gempa yang cukup tinggi, maka perlu adanya evaluasi terbaru mengenagi resiko gempa di Bendungan Wadaslintang. Analisis ini menggunakan metode <em>Probabilistic Seismic Hazard Analysis</em> (PSHA) dengan bantuan <em>software R-Crisis</em> 2018. Hasil analisis PSHA menunujukkan nilai percepatan tanah maksimum di lokasi tinjuan dengan periode ulang 500, 2.500, dan 10.000 tahun sebesar 0,22 g; 0,35 g dan 0,52 g. Hasil dari proses deagregasi menunjukkan besaran dan jarak gempa yang paling berpengaruh terhadap Bendungan Wadaslintang sebesar 6,87 – 7,13 Mw dan jarak 0-33 km. Hasil pencarian <em>ground motion, </em>didapatkan bahwa Gempa Irpinia, Italia (1980) mempunyai kriteria yang sama dengan lokasi tinjuan sesuai hasil deagregasi.  </p>

Probabilistic Seismic Hazard Analysis and Synthetic Ground Motion Generation for Seismic Risk Assessment of Structures in the Northeast India

2017 ◽  
Vol 8 (2) ◽  
pp. 39-59 ◽  
Author(s):  
Swarup Ghosh ◽  
Subrata Chakraborty
Keyword(s):  
Risk Assessment ◽  
Seismic Hazard ◽  
Ground Motion ◽  
Seismic Risk ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Seismic Risk Assessment ◽  
Site Specific

This article outlines the performance-based seismic risk assessment (PBSRA) of structures requiring probabilistic seismic hazard analysis (PSHA) to obtain hazard curves and an evaluation of the demand model by a nonlinear structural response analysis under properly selected ground motion records. Unfortunately, such site-specific information is not readily available for Northeast region of India. The present study focuses on these two aspects to supplement the PBSRA. The estimations of hazard curves are demonstrated by considering the seismicity within 300 km radius around the considered locations and specified exposure period. Due to limited availability of natural records in this region, synthetic accelerograms are generated using stochastic point source models by identifying the most contributing magnitude distance combinations from disaggregation of the PSHA results. The significant variabilities observed in the estimated hazard, synthetic accelerograms and nonlinear building responses in the various locations indicate the need of explicit site-specific analysis for PBRSA of structures in the region.

Determination of the Spatial Distribution Function of Bohai Seismic Tectonic Area

2014 ◽  
Vol 1065-1069 ◽  
pp. 1530-1534
Author(s):  
Zhuo Juan Xie ◽  
Yue Jun Lu
Keyword(s):  
Distribution Function ◽  
Spatial Distribution ◽  
Seismic Hazard ◽  
Seismic Activity ◽  
Hazard Analysis ◽  
Probabilistic Seismic Hazard Analysis ◽  
Seismic Hazard Analysis ◽  
Probabilistic Seismic Hazard ◽  
Spatial Distribution Function

The spatial distribution function assigns seismicity parameters of seismic zone and belt to the potential earthquake source area seismic by the magnitude interval, determination of the spatial distribution function is one of the key technologies to comprehensive probabilistic seismic hazard analysis methods, and the results will directly influence seismic hazard analysis results of the calculated sites. However, the spatial distribution functions are hard to get by statistics due to serious lack of seismic samples, and evaluation factors used in the actual work are too complex and not independent, the spatial distribution function is lack of reliability. In this paper, Bohai seismic tectonic area is chosen as an example; geological data are obtained from the newly built offshore oil platform engineering in recent decades, while seismic activity data are obtained by checking from historical difficult seismic parameters. Five factors are adopted in this area, including potential seismic focus area, seismic tectonic, seismic activity level, long-term forecasts, and strong earthquake recurrence interval and construct empty segment. Spatial distribution function of Bohai Sea earthquake structure area is obtained by weighted comprehension; it reflects the spatial and temporal heterogeneity of seismic activities in the area, and provides the calculation parameters for the probabilistic seismic hazard analysis.

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