地震动
强地震动
序列(生物学)
地震学
地质学
运动(物理)
峰值地面加速度
地理
大地测量学
计算机科学
人工智能
生物
遗传学
作者
Van-Bang Phung,Bor‐Shouh Huang,Cong-Nghia Nguyen,Van Duong Nguyen,Le-Minh Nguyen,Anh Duong Nguyen,Quang Khoi Le,The Truyen Pham,Thi Giang Ha,Quoc Van Dinh,Vinh Long Ha,Grigorios Lavrentiadis,Chung‐Han Chan,Dinh-Hai Pham
标识
DOI:10.1177/87552930241285177
摘要
It is challenging to select ground motion models (GMMs) for seismic hazard assessments for a region with sparse recorded data. In this study, data on the 2020 M w 5 Moc-Chau earthquake and its aftershocks were used to select an appropriate GMM for northern Vietnam (NVN). The 204 strong motion records were collected from 32 seismic stations and then used to compare eleven non-Vietnamese and two simplified Vietnamese local GMMs to assess their model prediction efficiencies. Among all the candidates, the global NGA-West2 GMMs performed the best fit with the data. Our analyses revealed the possibility of damage resulting from shaking in the Hanoi metropolitan area caused by recognized earthquake sources in NVN. In our examination of total residuals of differences between the GMM predictions and observed data, the average standard deviation from ASK14 was slightly higher than the limit accepted for modern seismic hazard assessments. ASK14 was further adjusted by the spatially varying coefficients that were derived from observations ground motion of this event. The adjusted ASK14 was used to evaluate seismic risk scenarios of large earthquakes in NVN and compared with the structures’ design spectra of the Hanoi area. To increase the prediction efficiency, additional local data are required to develop a region-specific GMM for NVN. We suggest that GMM be developed in the near future by regionalizing the ASK14 GMM according to additional local data further collected from existing broadband seismic observations and new accumulating continuous recording data from Vietnam’s broadband seismic networks.
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