In situ assessment of soil dynamic parameters for characterizing nonlinear seismic site response using KiK-net vertical array data

Wang, Haiyun; Jiang, Wei‐Ping; Wang, Su‐Yang; Miao, Yu

doi:10.1007/s10518-018-00539-3

Cited by 22 publications

(4 citation statements)

References 74 publications

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“…Table 1 lists the linear and hyperbolic model coefficients along with their p values for all of the NEHRP site classes defined in the Evaluation of Linear Site-Response Residuals section of the article as well as for NEHRP site classes A through CD and D through E from Figure 6 and all site classes combined (NEHRP site classes A through E). Figure 6 confirms the expectation that the relationship between PGA and I g is generally linear at small-to-moderate strains as predicted by the hyperbolic model and shown empirically by Wang et al (2018), Gue´guen (2016), Gue´guen et al (2019), and Kishida and Tsai (2021). The apparent deviations in this trend are discussed in the following section of the article.…”

Section: Pga Versus Strainsupporting

confidence: 84%

“…Figure 6 confirms the expectation that the relationship between PGA and I γ is generally linear at small-to-moderate strains as predicted by the hyperbolic model and shown empirically by Wang et al (2018), Guéguen (2016), Guéguen et al (2019), and Kishida and Tsai (2021). The apparent deviations in this trend are discussed in the following section of the article.…”

Section: Nonlinear Site Response and Shear Strainsupporting

confidence: 83%

“…However, shear stress and shear strain are not available for the C22 database or, for that matter, a strong-motion database that does not provide dynamic soil properties. When dynamic stress and strain are not available, it has been suggested that PGA can be used as a proxy for shear stress (Chandra et al, 2015(Chandra et al, , 2016Gue´guen, 2016;Gue´guen et al, 2019;Harmon et al, 2019;Idriss, 2011;Rathje et al, 2004;Wang et al, 2018) and that shearstrain index (I g ) can be used as a proxy for shear strain (Chandra et al, 2015(Chandra et al, , 2016Idriss, 2011;Kim et al, 2016;Wang et al, 2018). In this article, shear-strain index is defined as follows:…”

Section: Nonlinear Site Response and Shear Strainmentioning

confidence: 99%

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Empirical nonlinear site effects in Japanese megathrust earthquakes

Campbell¹,

Bozorgnia

Kuehn

et al. 2022

Earthquake Spectra

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In the course of developing ground-motion models (GMMs) of peak ground acceleration (PGA) for Japanese megathrust earthquakes, we discovered that empirical nonlinear site effects from these events are very different from those found for shallow crustal earthquakes in California and other global active tectonic regions. In particular, nonlinearity in site response is much less prominent in Japan than these other regions, which is consistent with other empirical and theoretical ground-response studies using recordings from both crustal and subduction earthquakes. In this study, we used the residuals from Japanese megathrust GMMs that account for linear site response to develop a nonlinear site-response term that uses the value of PGA on rock as a measure of ground-motion severity and the value of time-averaged shear-wave velocity in the top 30 m of a site ( VS30) as a measure of site properties. The resulting residuals are unbiased and trendless over all PGA values of interest. We also investigated whether soil nonlinearity can be modeled using proxies for shear stress and shear strain. We found deviations from expected linearity unrelated to nonlinear site effects at small values of strain—believed to be due to network accelerograph trigger thresholds—and at large earthquake magnitudes, believed to be due to the shape of the source spectrum.

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Section: Pga Versus Strainsupporting

confidence: 84%

Section: Nonlinear Site Response and Shear Strainsupporting

confidence: 83%

Section: Nonlinear Site Response and Shear Strainmentioning

confidence: 99%

See 1 more Smart Citation

Empirical nonlinear site effects in Japanese megathrust earthquakes

Campbell¹,

Bozorgnia

Kuehn

et al. 2022

Earthquake Spectra

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“…On one hand, besides the topography [38][39][40], the existence of soft interlayer can also change the propagation path of wave from bedrock to surface in comparison with corresponding regularly and horizontally stratified site and can significantly amplify or attenuate the ground motion [41][42][43]. On the other hand, it has long been recognized that, during strong ground motions, non-linear soil behavior tends to reduce site amplification at high frequencies due to the increase of damping and also tends to shift resonance frequencies of site toward lower frequencies due to the degradation of shear modulus [44][45][46][47][48][49][50].…”

Section: Introductionmentioning

confidence: 99%

Study on the Influence of a Soft Soil Interlayer on Spatially Varying Ground Motions

Yao

Miao

et al. 2022

Applied Sciences

Self Cite

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The existence of local soft interlayer can significantly amplify or attenuate the ground motion and thus might influence the lagged spatial coherency between spatially varying earthquake ground motions. A target site with a local soft interlayer was assumed first, and then two numerical examples were set. In example 1, linear soil behavior was considered and a large amount of quasi-stationary spatially varying earthquake ground motions were generated by combining the one-dimensional wave propagation theory and the classical spectral representation method. The influence regularity of varying shear wave velocity, buried depth, and thickness of the soft interlayer on the characteristics of lagged spatial coherency was investigated. In example 2, non-linear soil behavior was taken into account and fully non-stationary spatially varying earthquake ground motions were thus generated by using time-varying transfer function and spectral representation method. An overall evaluation was carried out to shed light on the differences of characteristics of spatial coherency between non-linear soil and linear soil cases. It showed that: (i) As the shear wave velocity of interlayer declines and as the buried depth and thickness increase, remarkable reduction of spatial coherency showed up; (ii) the reduction of lagged spatial coherency caused by varying buried depth may be more inclined to concentrate in the lower frequency range; (iii) the non-linear soil behavior can cause greater further reduction of lagged spatial coherency in comparison with linear soil behavior, especially in the higher frequency range; (iv) the troughs of lagged spatial coherency curve tend to be located in the variation range of vibration frequency of time-varying spectral ratio.

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