Spatial Correlation of Peak Ground Motions and Pseudo-Spectral Acceleration Based on the Sarpol-e-Zahab Mw 7.3, 2017 Earthquake Data

余震 空间相关性 地质学 地震学 峰值地面加速度 光谱加速度 加速度 航程(航空) 残余物 大地测量学 震中 震级(天文学) 相关函数(量子场论) 地震动 物理 光谱密度 统计 数学 算法 材料科学 经典力学 天文 复合材料
作者
Hamid Zafarani,Seyyed Mohammad Mahdi Ghafoori,M. R. Soghrat,Mahsa Shafiee
出处
期刊:Annals of Geophysics [Instituto Nazionale di Geofisica e Vulcanologia, INGV]
卷期号:63 (4) 被引量:1
标识
DOI:10.4401/ag-8349
摘要

Ground motion intensity measures and structural responses are correlated in nearby sites. The value of this correlation relies on some parameters such as the local geology and distance between the two sites and the natural period of structures, particularly, when lifeline systems or distributed structures are of concern, the issue becomes more important. In this study, the spatial correlation of peak ground acceleration and Spectral Acceleration are evaluated as a function of inter-site separation distance for the Mw7.3 Sarpol-e-Zahab earthquake. On 12 November 2017 a large earthquake occurred near the western border of Iran. The epicenter of the earthquake was reported at 34.77 N and 45.76 E. Here, 192 pairs of horizontal components from the above-mentioned event and 35 of its larger aftershocks with magnitude ranging from Mw 4.0 to 7.3 are employed to evaluate the intra-event residual correlation by considering two Ground Motion Prediction Equations (GMPEs) proposed by Akkar and Bommer [2010] and Zafarani et al. [2017]. A correlation analysis is carried out through semivariogram as a powerful geostatistical tool. As a skeleton for correlation modeling, a kind of exponential model is used. According to the proposed model, the results show that the overall trend of correlation Range depends on spectral period. The results demonstrate that there is strong spatial correlation in the proposed model obtained from the Sarpol-e- Zahab ground motions. The model provided in this study could be employed in earthquake engineering implements such as Shakemaps [Wald et al., 1999] whenever spatial correlation models are required.

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