Because of the limited number of strong‐motion records that have measured ground response at large strains, any statistical analyses of seismic site‐response models subject to strong ground motions are severely limited by a small number of observations. Recent earthquakes in Japan, including the M w 9.0 Tohoku earthquake of March 2011, have substantially increased the observations of strong‐motion records that can be used to compare alternative site‐response models at large strains and can subsequently provide insight into the accuracy and precision of site‐response models. Using the Kiban‐Kyoshin network (KiK‐net) downhole array data in Japan, we analyze the accuracy (bias) and variability (precision) resulting from common site‐response modeling assumptions, and we identify critical parameters that significantly contribute to the uncertainty in site‐response analyses. We perform linear and equivalent‐linear site‐response analyses at 100 KiK‐net sites using 3720 ground motions ranging in amplitude from weak to strong; 204 of these records have peak ground accelerations greater than ![Graphic][1] at the ground surface. We find that the maximum shear strain in the soil profile, the observed peak ground acceleration at the ground surface, and the predominant spectral period of the surface ground motion are the best predictors of where the evaluated models become inaccurate and/or imprecise. The peak shear strains beyond which linear analyses become inaccurate in predicting surface pseudospectral accelerations (PSA; presumably as a result of nonlinear soil behavior) are a function of vibration period and are between 0.01% and 0.1% for periods 0.5  s do not display noticeable effects of nonlinear soil behavior.

Online Material: Site‐specific information and model residuals at 100 KiK‐net stations.

 [1]: /embed/inline-graphic-1.gif

Critical Parameters Affecting Bias and Variability in Site‐Response Analyses Using KiK‐net Downhole Array Data

Probabilistic seismic hazard analyses are usually performed with semi-empirical ground motion models (GMMs) following the ergodic assumption whereby average source, path, and site effects from glob...

Non-Ergodic Site Response in Seismic Hazard Analysis:

The last decade of performance-based earthquake engineering (PBEE) research has seen a rapidly increasing emphasis placed on the explicit quantification of uncertainties. This paper examines uncertainty consideration in input ground-motion and numerical seismic response analyses as part of PBEE, with particular attention given to the physical consistency and completeness of uncertainty consideration. It is argued that the use of the commonly adopted incremental dynamic analysis leads to a biased representation of the seismic intensity and that when considering the number of ground motions to be used in seismic response analyses, attention should be given to both reducing parameter estimation uncertainty and also limiting ground-motion selection bias. Research into uncertainties in system-specific numerical seismic response analysis models to date has been largely restricted to the consideration of ‘low-level’ constitutive model parameter uncertainties. However, ‘high-level’ constitutive model and model methodology uncertainties are likely significant and therefore represent a key research area in the coming years. It is also argued that the common omission of high-level seismic response analysis modelling uncertainties leads to a fallacy that ground-motion uncertainty is more significant than numerical modelling uncertainty. The author’s opinion of the role of uncertainty analysis in PBEE is also presented. Copyright © 2013 John Wiley & Sons, Ltd. Received 3 December 2012; Revised 14 May 2013; Accepted 20 May 2013

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A critical examination of seismic response uncertainty analysis in earthquake engineering

Measured vs. predicted site response at the Garner Valley Downhole Array considering shear wave velocity uncertainty from borehole and surface wave methods

A number of strategies exist to account for the epistemic uncertainty and aleatory variability in shear-wave velocity (Vs) profiles used in site response analyses. Epistemic uncertainty may be accounted for by using median and bounding-type profiles (e.g., ±20%), while aleatory variability may be accounted for by using Vs randomization procedures. A robust, quantitative method to help judge how well these statistically derived Vs profiles represent actual subsurface stiffness or layering conditions is currently not available. This paper presents a surface-wave dispersion approach for evaluating statistical models meant to account for Vs uncertainty in site response. Specifically, surface-wave dispersion data from two geologically disparate sites were used to generate 1,000  Vs profiles and layered earth models whose theoretical dispersion curves fit within the uncertainty bounds of the experimental data collected at each site. Additionally, theoretical dispersion curves generated from statistical ...

Surface-Wave Dispersion Approach for Evaluating Statistical Models That Account for Shear-Wave Velocity Uncertainty

Seismic site response analysis evaluates the influence of local soil conditions on earthquake ground shaking. There are multiple sources of potential uncertainty in this analysis; the most significant pertaining to the specification of the input motions and to the characterization of the soil properties. The influence of the selection of input ground motions on equivalent-linear site response analysis is evaluated through analyses performed with multiple suites of input motions selected to fit the same target acceleration response spectrum. The results indicate that a stable median surface response spectrum (i.e., within ±20% of any other suite) can be obtained with as few as five motions, if the motions fit the input target spectrum well. The stability of the median is improved to ±5 to 10% when 10 or 20 input motions are used. If the standard deviation of the surface response spectra is required, at least 10 motions (and preferably 20) are required to adequately model the standard deviation. The influence of soil characterization uncertainty is assessed through Monte Carlo simulations, where variations in the shear-wave velocity profile and nonlinear soil properties are considered. Modeling shear-wave velocity variability generally reduces the predicted median surface motions and amplification factors, most significantly at periods less than the site period. Modeling the variability in nonlinear properties has a similar, although slightly smaller, effect. Finally, including the variability in soil properties significantly increases the standard deviation of the amplification factors but has a lesser effect on the standard deviation of the surface motions.

Whitney L. Trent

Papers

Influence of Input Motion and Site Property Variabilities on Seismic Site Response Analysis