[S-SS06] Seismic wave propagation: Theory and Application

[SSS06-P02] Quantifying the nonlinearity of strong-motion waveforms due to liquefaction using recurrence plots: The case of the 2016 Fukushima earthquake recorded on S-net

*Tomoya Muramoto^1,2, Hisahiko Kubo³, Noriyuki Furuichi² (1.Graduate school of faculty of science, Kyoto university, 2.National Metrology Institute of Japan, National Institute of Advanced Industrial Science and Technology, 3.National Research Institute for Earth Science and Disaster Resilience)

It is known that strong motion recorded by seafloor seismographs sometimes contain waveforms with strong nonlinearity due to liquefaction of the installation surface (e.g., Kubo et al., 2019). In this study, we developed an analysis method to quantitatively evaluate the nonlinearity of waveforms caused by liquefaction in strong motion using cross-recurrence quantification analysis. Cross-recurrence quantification analysis is an analysis performed on time series visualized by recurrence plots (e.g., Eckmann et al., 1987; Marwan et al., 2007), and has recently begun to be used in the field of solid-state geophysics (e.g., Hobbs and Ord, 2018). Although this is a simple definition of the recurrence plot, it reveals a variety of information about the dynamical system behind the time series data (Marwan et al., 2007). The advantage of using cross-recurrence quantification analysis to evaluate the nonlinearity of strong motion is that multiple indices equivalent to entropy and Lyapunov exponents can be calculated in the same framework (Marwan et al., 2002). In this study, we calculated the entropy of the patterns of diagonal, vertical, and horizontal lines of the recurrence plot as the characteristic quantities. In order to examine whether the obtained entropies are representative of the nonlinearity of strong motion, we compared them with the maximum acceleration (PGA) according to Kubo et al. (2019). In this study, we also investigated the dimensionality and delay time dependence of the attractor constructed to calculate the recurrence plot.
The developed analysis method was applied to the strong motion of the S-net that recorded the 2016 Fukushima-oki earthquake. Since the epicenter of the earthquake was located near the S-net, the strong motion is expected to show strong nonlinearity. By applying the method proposed in this paper, it is confirmed that there is a hierarchical structure in each waveform, especially in the subsequent waves. These results fully support our aim to quantitatively evaluate the nonlinearity of waveforms caused by liquefaction in strong motions using cross-recurrence quantification analysis.