Influence of Sensor Density on Seismic Damage Assessment: A Case Study for Istanbul

Qingle Cheng, Yifan Fei, Xinzheng Lu, Wenjie Liao, Wenyang Zhang, Peng Yu Chen, Asli Kurtulus, Farid Ghahari, Viviana Vela, Ertugrul Taciroglu

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

The strong ground motions (GMs) recorded by strong motion networks are significant to increase the accuracy of seismic damage assessment. However, the influence of sensor density on seismic damage assessment remains unclarified. Therefore, a workflow is proposed in this study to quantitatively analyze the influence of sensor density on seismic damage assessment. The scenario-based earthquake simulation method is first used to provide the time history of GM at each location as the ground truth of the analysis. Subsequently, a GM prediction method, namely the interpolation method, is adopted to predict GMs at locations without sensors using measuring data from the limited sensors. Finally, the building scale and region scale seismic damage under different sensor densities are compared to quantitatively analyze the influence of sensor density on seismic damage assessment. A detailed case study for Zeytinburnu District, Istanbul, Turkey, is performed to demonstrate the proposed methods. The findings of this study can provide an important reference for seismic damage assessment and the deployment of strong motion networks.

Original languageEnglish
Pages (from-to)2156-2169
Number of pages14
JournalBulletin of the Seismological Society of America
Volume112
Issue number4
DOIs
StatePublished - Aug 2022

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