Analysis of Single-Station Standard Deviation Using the KiK-net Data

Self Cite

149

100

Aleatory variability in ground-motion prediction, represented by the standard deviation (sigma) of a ground-motion prediction equation, exerts a very strong influence on the results of probabilistic seismic-hazard analysis (PSHA). This is especially so at the low annual exceedance frequencies considered for nuclear facilities; in these cases, even small reductions in sigma can have a marked effect on the hazard estimates. Proper separation and quantification of aleatory variability and epistemic uncertainty can lead to defensible reductions in sigma. One such approach is the single-station sigma concept, which removes that part of sigma corresponding to repeatable site-specific effects. However, the site-to-site component must then be constrained by site-specific measurements or else modeled as epistemic uncertainty and incorporated into the modeling of site effects. The practical application of the single-station sigma concept, including the characterization of the dynamic properties of the site and the incorporation of site-response effects into the hazard calculations, is illustrated for a PSHA conducted at a rock site under consideration for the potential construction of a nuclear power plant.

Section: Sigma and The Partially Nonergodic Approachmentioning

confidence: 99%

Section: Estimation Of the Site Term And Its Epistemic Uncertaintymentioning

confidence: 99%

Application of Single-Station Sigma and Site-Response Characterization in a Probabilistic Seismic-Hazard Analysis for a New Nuclear Site

Rodríguez-Marek¹,

Rathje²,

Bommer³

et al. 2014

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149

100

“…Thanks to the increasing availability of strong-motion records, several recent studies propose to refine groundmotion variability analyses by splitting sigma into various component (e.g., Chen and Tsai, 2002;Al-Atik et al, 2010;Rodriguez-Marek et al, 2011;Edwards and Fäh, 2013). Following the notation of Al-Atik et al (2010), the total variability can then be expressed as σ tot ϕ 2 τ 2 q ;…”

Section: Introductionmentioning

confidence: 99%

Is Ground‐Motion Variability Distance Dependent? Insight from Finite‐Source Rupture Simulations

Imtiaz¹,

Causse²,

Chaljub³

et al. 2015

The ground-motion variability sigma is a fundamental component in probabilistic seismic-hazard assessment because it controls the hazard level at very low probabilities of exceedance. So far, most of the analyses based on empirical ground-motion prediction equations do not consider any distance dependency of sigma. This study aims to analyze the potential distance dependency of ground-motion variability, especially in the near-field region, where the variability is poorly constrained due to the lack of available records. We, therefore, investigate the distance dependency of sigma by performing numerical simulations of ground motion for some strike-slip events. Synthetic velocity seismograms (up to 3 Hz) have been generated from a suite of finite-source rupture models of past earthquakes. Green's functions were calculated for a 1D velocity structure using a discrete wavenumber technique (Bouchon, 1981). The within-event component of the ground-motion variability was then evaluated from the synthetic data as a function of distance. The simulations reveal that the within-event component of the ground motion shows a distance dependency, subject to the rupture type. For bilateral ruptures, the variability tends to increase with distance. On the contrary, in case of unilateral events, the variability decreases with distance.

“…A similar plot as a function of peak strain instead of PGA would exhibit a larger continuity between results of both input waveforms; (c) the larger σ PGA values for NL computations compared with the linear case (except for the very specific case of linear-elastic response with rigid boundary conditions, discussed later); (d) the maximum obtained σ PGA value (0.15) remains below the specific single-station, within-event variability Φ SS;PGA value for a site with a V S30 equivalent to P1 (Rodriguez-Marek et al, 2011), which is around 0.2. The uncertainties linked with the NL simulations remain below the natural single site response variability (at least for PGA values not exceeding 5 m=s 2 and the very peculiar and simplified input wavefield considered here, consisting of pure vertically incident plane S waves.…”

Section: Epistemic Uncertainty Quantification Of the Variability Of Tmentioning

confidence: 99%

International Benchmark on Numerical Simulations for 1D, Nonlinear Site Response (PRENOLIN): Verification Phase Based on Canonical Cases

Régnier¹,

Bonilla²,

Bard³

et al. 2016

PREdiction of NOn-LINear soil behavior (PRENOLIN) is an international benchmark aiming to test multiple numerical simulation codes that are capable of predicting nonlinear seismic site response with various constitutive models. One of the objectives of this project is the assessment of the uncertainties associated with nonlinear simulation of 1D site effects. A first verification phase (i.e., comparison between numerical codes on simple idealistic cases) will be followed by a validation phase, comparing the predictions of such numerical estimations with actual strongmotion recordings obtained at well-known sites. The benchmark presently involves 21 teams and 23 different computational codes.We present here the main results of the verification phase dealing with simple cases. Three different idealized soil profiles were tested over a wide range of shear strains with different input motions and different boundary conditions at the sediment/bedrock interface. A first iteration focusing on the elastic and viscoelastic cases was proved to be useful to ensure a common understanding and to identify numerical issues before pursuing the nonlinear modeling. Besides minor mistakes in the implementation of input parameters and output units, the initial discrepancies between the numerical results can be attributed to (1) different understanding of the expression "input motion" in different communities, and (2) different implementations of material damping and possible numerical energy dissipation. The second round of computations thus allowed a convergence of all teams to the Haskell-Thomson analytical solution in elastic and viscoelastic cases. For nonlinear computations, we investigate the epistemic uncertainties related only to wave propagation modeling using different nonlinear constitutive models. Such epistemic uncertainties are shown to increase with the strain level and to reach values around 0.2 (log 10 scale) for a peak ground acceleration of 5 m=s 2 at the base of the soil column, which may be reduced by almost 50% when the various constitutive models used the same shear strength and damping implementation.