Recording-based identification of site liquefaction

• Published in: Earthquake Engineering and Engineering Vibration Vol. 4; no. 2; pp. 181 - 189
• Main Authors: Hu, Yuxian, Zhang, Yushan, Liang, Jianwen, Zhang, Ray Ruichong
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Nature B.V 01.12.2005; Institute of Geophysics, China Earthquake Administration, Beijing 100081, China%Department of Civil Engineering, Tianjin University, Tianjin 300072, China%Division of Engineering, Colorado School of Mines, Golden, CO 80401, USA
• Subjects: Earthquakes; Fourier transforms; Frequency analysis; Ground motion; Liquefaction; Seismic activity; Seismic engineering; Seismic hazard; Seismic waves; Structural engineering; site condition; liquefaction detection; Hilbert-Huang transform; predominant instantaneous frequency
• ISSN: 1671-3664; 1993-503X
• DOI: 10.1007/s11803-005-0001-3

Reconnaissance reports and pertinent research on seismic hazards show that liquefaction is one of the key sources of damage to geotechnical and structural engineering systems. Therefore, identifying site liquefaction conditions plays an important role in seismic hazard mitigation. One of the widely used approaches for detecting liquefaction is based on the time-frequency analysis of ground motion recordings, in which short-time Fourier transform is typically used. It is known that recordings at a site with liquefaction are the result of nonlinear responses of seismic waves propagating in the liquefied layers underneath the site. Moreover, Fourier transform is not effective in characterizing such dynamic features as time-dependent frequency of the recordings rooted in nonlinear responses. Therefore, the aforementioned approach may not be intrinsically effective in detecting liquefaction. An alternative to the Fourier-based approach is presented in this study, which proposes time-frequency analysis of earthquake ground motion recordings with the aid of the Hilbert-Huang transform (HHT), and offers justification for the HHT in addressing the liquefaction features shown in the recordings. The paper then defines the predominant instantaneous frequency (PIF) and introduces the PIF-related motion features to identify liquefaction conditions at a given site. Analysis of 29 recorded data sets at different site conditions shows that the proposed approach is effective in detecting site liquefaction in comparison with other methods.