Evaluating the identification methods of permanent displacement derived from strong motion records: Case studies in the 2023 Turkey–Syria earthquake

Author:

Zhou Baofeng12,Guo Wenxuan12ORCID,Ren Yefei12,Wen Ruizhi12,Wang Hongwei12,Xu Tong12,Zhang Cong12,Liu Aiwen3

Affiliation:

1. Key Laboratory of Earthquake Engineering and Engineering Vibration Institute of Engineering Mechanics, China Earthquake Administration Harbin China

2. Key Laboratory of Earthquake Disaster Mitigation Ministry of Emergency Harbin Heilongjiang China

3. Institute of Geophysics China Earthquake Administration Beijing China

Abstract

AbstractOn February 6, 2023, the Republic of Turkey experienced a rare occurrence of two successive earthquakes, each with a magnitude exceeding 7.0. The Disaster and Emergency Management Agency (AFAD) swiftly shared the strong motion records, thereby enriching the global database of near‐fault strong motion records. Identification of permanent displacement is essential for effectively utilizing these records. In this study, we refined the permanent displacement identification method, which combines the Hermit interpolation baseline correction with flatness determination by incorporating a low‐pass filter. Following this, we compared four permanent displacement identification methods, including our improved approach. We applied these to the strong motion record of station 4404 and compared the results with the Global Positioning System coseismic displacement. At the same time, we used field investigation data to verify the effectiveness of our improved method, studying its applicability for both single‐wave packet and multiwave packet records. The conclusions are the following: the improved method provides a more reasonable and effective means of identifying permanent displacement. When the peak ground acceleration (PGA) exceeds 1 g, the permanent displacement identifications from the four methods differ significantly. The discrepancy in permanent displacements identified by the four methods in the horizontal direction is larger than that in the U−D direction. For the record with the largest PGA (station 4614), our improved method yields more reasonable results compared with other techniques. Furthermore, the choice of segmentation time nodes in the velocity time history significantly affects the identification of permanent displacement.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Heilongjiang Province

Publisher

Wiley

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