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Multi-temporal analysis of ambient noise polarization to characterize site response in the town of Amatrice, shattered by the 2016 Central Italy earthquake
Geophysical Journal International ( IF 2.8 ) Pub Date : 2020-09-18 , DOI: 10.1093/gji/ggaa335
Vincenzo Del Gaudio 1 , Janusz Wasowski 2 , Pierpaolo Pierri 1 , Antonio Moretti 3 , Gianluca Ferrini 3
Affiliation  

The Mw 6.0 earthquake that hit central Italy on 24 August 2016 caused an abnormally high level of destruction in the town of Amatrice. In order to clarify the role of site response in causing such a disaster, a series of ambient noise recordings acquired in the aftermath of the event are analysed here to identify site resonance properties from the ratios H/V between horizontal and vertical amplitudes of ground motion. Although the noise data acquisition was limited by the emergency management activities, the use of a new analysis technique, which isolates the contribution of Rayleigh waves to the noise wavefield and averages instantaneous estimates of H/V ratios, provided more stable results compared to the standard Nakamura's technique based on mean spectral ratios. The results demonstrated the occurrence of significant resonance phenomena, but without an obvious correlation with the spatial distribution of damage severity. It is apparent that the damage severity was also influenced by some additional local factors related to building vulnerability. Moreover, the time series analysis revealed seasonal variations in the Rayleigh wave ellipticity curves likely related to the water content changes in the surface deposits and their influence on the Poisson coefficient. Finally, the new method proved capable of recognizing time-varying directions of Rayleigh wave propagation. This capability could be exploited to support other passive seismic methods (e.g. ReMi), whose results reliability is limited by the lack of control on wave direction origin.

中文翻译:

多时相分析环境噪声极化以表征Amatrice镇的现场响应,2016年意大利中部地震打破了这一点

2016年8月24日,意大利中部发生的6.0级Mw地震在Amatrice镇造成了异常高的破坏力。为了阐明现场响应在造成此类灾难中的作用,此处分析了事件发生后采集的一系列环境噪声记录,以根据地面运动的水平和垂直幅度之间的比率H / V识别现场共振特性。 。尽管噪声数据的采集受到应急管理活动的限制,但是使用一种新的分析技术可以将瑞利波对噪声波场的影响隔离开来,并且可以对H / V比的瞬时平均值进行平均,与标准相比,该方法提供了更稳定的结果Nakamura的技术基于平均光谱比率。结果表明发生了明显的共振现象,但与损害严重性的空间分布没有明显的相关性。显然,损坏的严重程度还受到与建筑物易损性有关的一些其他本地因素的影响。此外,时间序列分析显示瑞利波椭圆率曲线的季节性变化可能与表层沉积物中的水含量变化及其对泊松系数的影响有关。最终,该新方法被证明能够识别瑞利波传播的时变方向。可以利用此功能来支持其他被动地震方法(例如ReMi),其结果可靠性受到对波方向原点缺乏控制的限制。显然,损坏的严重程度还受到与建筑物易损性有关的一些其他本地因素的影响。此外,时间序列分析显示瑞利波椭圆率曲线的季节性变化可能与表层沉积物中的水含量变化及其对泊松系数的影响有关。最终,该新方法被证明能够识别瑞利波传播的时变方向。可以利用此功能来支持其他被动地震方法(例如ReMi),其结果可靠性受到对波方向原点缺乏控制的限制。显然,损坏的严重程度还受到与建筑物易损性有关的一些其他本地因素的影响。此外,时间序列分析显示瑞利波椭圆率曲线的季节性变化可能与表层沉积物中的水含量变化及其对泊松系数的影响有关。最终,该新方法被证明能够识别瑞利波传播的时变方向。可以利用此功能来支持其他被动地震方法(例如ReMi),其结果可靠性受到对波方向原点缺乏控制的限制。时间序列分析表明,瑞利波椭圆率曲线的季节性变化可能与表层沉积物中的水含量变化及其对泊松系数的影响有关。最终,该新方法被证明能够识别瑞利波传播的时变方向。可以利用此功能来支持其他被动地震方法(例如ReMi),其结果可靠性受到对波方向原点缺乏控制的限制。时间序列分析表明,瑞利波椭圆率曲线的季节性变化可能与表层沉积物中的水含量变化及其对泊松系数的影响有关。最终,该新方法被证明能够识别瑞利波传播的时变方向。可以利用此功能来支持其他被动地震方法(例如ReMi),其结果可靠性受到对波方向原点缺乏控制的限制。
更新日期:2020-09-20
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