1 results for Conference poster, 1D Nonlinear site response prediction: Analysis of residuals at a large number of KikNet vertical seismometer arrays

1D Nonlinear site response prediction: Analysis of residuals at a large number of KikNet vertical seismometer arrays
Kaklamanos, J.; Bradley, B.A. (2015)
Conference poster
University of Canterbury LibrarySite response models are frequently used in engineering practice to predict surficial ground motions based on a sitespecific soil profile and input motions, and site response predictions are especially important for large strains and accelerations, which have a greater damage potential. To characterize nonlinear soil behavior at large strains, a number of constitutive soil models have been developed. However, the application of fully nonlinear timedomain site response analyses remains limited in practice, with the equivalentlinear site response approximation to nonlinear soil behavior, using frequencydomain programs such as SHAKE (Schnabel et al., 1972), still the most common approach. For a particular project, engineering practitioners are therefore faced with the challenge of selecting the appropriate level of model complexity (e.g., equivalentlinear vs. nonlinear). While previous validation studies have attempted to quantify the levels of ground motion for which nonlinear site response analyses are necessary (e.g., Assimaki et al., 2008; Kwok et al., 2008; Kim and Hashash, 2013; Kaklamanos et al., 2015), the assessment of fully nonlinear site response models is often limited to a relatively small number of sites and ground motions. In this study, onedimensional (1D) totalstress nonlinear, equivalent linear, and linear site response predictions are calculated using an unprecedented number of sites and ground motions, allowing for more statistically significant conclusions to be drawn than in prior studies. This study uses Japan’s comprehensive KibanKyoshin network of vertical seismometer arrays (Aoi et al., 2000), in particular, 5626 ground motions at 114 KiKnet sites are utilized, with 239 ground motions having PGA > 0.3g. Site response predictions are calculated using the program DEEPSOIL (Hashash et al., 2011), and SHAKE for the nonlinear, and equivalent linear analyses, respectively; based on the P and S wave velocity profiles, and soil types provided on the KiKNet database. The Zhang et al. (2005) modulusreduction and damping curves are used in the equivalentlinear analyses and as the target curves for the nonlinear analyses. This study builds upon prior work (Kaklamanos et al., 2013) in which linear and equivalentlinear site response analyses (but not nonlinear analyses) were performed at 100 KiKnet sites using 3720 ground motions, allowing for broad conclusions on the uncertainty of linear and equivalentlinear site response models. With the large database of nonlinear site response model predictions in the current study, the predictive capabilities of fully nonlinear totalstress site response models relative to linear and equivalentlinear models are assessed. The model residuals assessed in this study are those of the 5%damped pseudoacceleration response spectra, calculated as ln(PSAobs) – ln(PSApred), where PSAobs and PSApred are the observed and predicted spectral accelerations at a given period, respectively. From analyzing the trends of the model residuals versus the maximum shear strain in the soil profile, Kaklamanos et al. (2013) concluded that the equivalentlinear model becomes inaccurate when strains exceed 0.1 to 0.4%. In the current study, we find that the model residuals of the equivalentlinear and nonlinear site response models generally do not deviate from each other significantly at large shear strains. For shear strains greater than 0.5% at short spectral periods, both the equivalentlinear and nonlinear model residual plots slope upwards, indicating that these models tend to underpredict largestrain ground motions. However, the nonlinear model residuals do not slope upward as significantly at some spectral periods (for example, for spectral 1 accelerations at T = 0.1 s). Furthermore, the scatter in the equivalentlinear model residuals is greater than that of the nonlinear model residuals at large shear strains, suggesting that the equivalentlinear site response model is less precise at large shear strains. In the aggregate, the linear, equivalentlinear, and nonlinear model biases and standard deviations can be calculated across all sites and ground motions using mixedeffects regression on the model residuals. Comparisons of the model biases and standard deviations indicate that all 1D site response models (linear, equivalentlinear, and nonlinear) are biased towards underprediction of ground motions at short spectral periods, where nonlinear effects are strongest. However, the equivalentlinear and nonlinear model biases are smaller than the linear model bias. The persistent model biases suggest that: (1) many of these sites may experience a breakdown in the 1D siteresponse assumptions; and/or (2) the site investigation data provided on KiKnet (i.e. velocity profiles and broad soil type) may be oversimplified. With respect to the first point, in particular, the underlying assumptions of 1D site response may have to be addressed in order to make notable prediction improvements, perhaps by incorporation of threedimensional soil constitutive response and incident ground motion effects. Based on the intersite residuals, we have also identified some “interesting” sites at which all 1D site response models most strongly overpredict or underpredict ground motions: ISKH05 and KOCH05 are characterized by the strongest underpredictions, and HYGH07, IWTH07, and WKYH01 are characterized by the strongest overpredictions (at different vibration periods, however). Because these sitespecific biases are consistent across all 1D site response models, the 1D site response assumption is likely not valid at these sites. Although the nonlinear site response models are shown to offer an improvement over equivalentlinear models, the remaining trends in the nonlinear model residuals suggest that other factors—such as threedimensional effects—have a significant impact on site response behavior.
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