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

Griffiths, Shawn C.; Cox, Brady R.; Rathje, Ellen M.; Teague, David P.

doi:10.1061/(asce)gt.1943-5606.0001552

Cited by 75 publications

(42 citation statements)

References 32 publications

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“…The number 50 was chosen because it is manageable, from a computational standpoint, and because 50 Vs profiles chosen randomly from the population of the best 1,000 Vs profiles was found to statistically reproduce the same median and standard deviation as the population of 1,000. The same conclusions were reached at the two sites discussed in Griffiths et al (2016a) [8]. Thus, 350 total Vs profiles resulting from surface wave inversion were selected for site response (i.e., 50 Vs profiles from 7 unique inversions of the same dataset).…”

Section: Vs Profiles Derived From the Layering Ratio Surface Wave Invmentioning

confidence: 54%

“…If abundant Vs data is available at a site, the statistical parameters needed to constrain epistemic uncertainty and aleatory variability can be obtained. Otherwise, conservative estimates must be made (Griffiths et al 2016a [8]).…”

Section: Introductionmentioning

confidence: 99%

“…A companion study documented by Griffiths et al (2016a and 2016b) [8], [19] investigated site response variability at two sites (one with a strong impedance contrast and one without) using many Vs profiles derived directly from a single surface wave inversion and from several statistically-based methods commonly used to account for epistemic uncertainty and aleatory variability. In the initial study, Griffiths et al (2016a) [8] argued that the experimentally-measured dispersion data represents the "site signature", which reveals important information about wave propagation across the site, and any Vs profiles that fail to capture the site signature (i.e., fail to match the experimental dispersion data) may not be appropriate for trying to quantify the variability in site response. Inherent in this argument is the assumption that a broadband, high-quality experimental dispersion curve has been obtained and demonstrated to be representative of the site.…”

Section: Introductionmentioning

confidence: 99%

“…Griffiths et al (2016a) [8] found that theoretical dispersion curves associated with upper/lower range Vs profiles (e.g., median +/-20%) commonly used to account for epistemic uncertainty (e.g. Matasovic and Hashash 2012 [25], EPRI 2012 [7]) yielded a poor fit to the experimental dispersion data (i.e., relatively high misfit values) measured at their study sites.…”

Section: Introductionmentioning

confidence: 99%

“…While the uncertainty associated with the inversion itself is purely epistemic, the data used as input into the inversion (i.e., the experimental dispersion data) is influenced by both aleatory variability and epistemic uncertainty. Therefore, the final Vs profiles derived directly from surface wave testing are influenced by both sources of uncertainty and it would be very difficult to decouple them (Griffiths et al 2016a [8]). In this study, no attempt was made to do so.…”

Section: Introductionmentioning

confidence: 99%

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Site response implications associated with using non-unique Vs profiles from surface wave inversion in comparison with other commonly used methods of accounting for Vs uncertainty

Teague

Cox

2016

Soil Dynamics and Earthquake Engineering

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This paper discusses variability and accuracy of site response predictions performed using shear wave velocity (Vs) profiles derived from non-unique surface wave inversions and other commonly used statistical methods of accounting for epistemic uncertainty and aleatory variability in Vs. Specifically, linear and equivalent linear site response analyses were performed on the following three classes of Vs profiles: (1) 350 Vs profiles developed by performing multiple surface wave inversions, each with a unique set of layering parameters, on a common dispersion dataset, (2) two upper/lower range base-case Vs profiles developed by systematically increasing or decreasing the solution Vs profile by 20%, and (3) 100 Vs profiles developed using the Vs randomization procedure proposed by Toro (1995). Vs profiles derived from surface wave inversions generally yielded accurate site response estimates with minimal variability, so long as their theoretical dispersion data fit the experimental dispersion data well. On the other hand, the upper/lower range and randomized Vs profiles generally produced inaccurate and highly variable site response predictions, although the inclusion of site-specific parameters in the randomization model improved the results. At real sites where substantial aleatory variability is anticipated and/or the epistemic uncertainty is quite high, the site response estimates associated with the randomized and/or upper/lower range Vs profiles may be deemed acceptable. However, if the experimental dispersion data and horizontal-to-vertical spectral ratios are shown to be consistent over the footprint of a site, it may be possible to significantly reduce the uncertainty associated with the input Vs profile and the resulting uncertainty in the site response.

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Section: Vs Profiles Derived From the Layering Ratio Surface Wave Invmentioning

confidence: 54%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Site response implications associated with using non-unique Vs profiles from surface wave inversion in comparison with other commonly used methods of accounting for Vs uncertainty

Teague

Cox

2016

Soil Dynamics and Earthquake Engineering

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Forward modeling of Rayleigh surface waves for analytical characterization of dominant dispersion trends

Lin

Ashlock

et al. 2021

Earthq Engng Struct Dyn

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Forward modeling is of critical importance for inversion analysis of surface wave methods to obtain shear‐wave velocity (VS) profiles of soil sites. The dynamic stiffness matrix (DSM) method can provide forward modeling of Rayleigh surface waves to simulate complex wave propagation in layered soil sites. However, contamination from body waves and interference of multiple Rayleigh wave modes can reduce the accuracy of theoretical dispersion curves, especially at irregular soil sites with embedded low‐velocity or high‐velocity layers. An analytical method is developed herein to combine the techniques of the multichannel analysis of surface waves method with the DSM method to improve the accuracy of the theoretical dispersion analysis for soil sites. The proposed method implements multichannel analysis of the analytical displacement responses to capture dominant dispersion trends. Comparison of the results obtained with the new method against those from the transfer matrix method and the literature indicates that the new method can (1) effectively minimize the effects of contamination caused by body waves and interference from several Rayleigh wave modes, and (2) generate accurate dominant dispersion trends for soil sites with various stiffness profiles, especially for the high‐frequency dispersion characteristics of the profiles with embedded low‐velocity layers.

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A probabilistic investigation on the dynamic behaviour of pile foundations in homogeneous soils

Minnucci

Morici

Carbonari

et al. 2021

Bull Earthquake Eng

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

Cited by 75 publications

References 32 publications

Site response implications associated with using non-unique Vs profiles from surface wave inversion in comparison with other commonly used methods of accounting for Vs uncertainty

Site response implications associated with using non-unique Vs profiles from surface wave inversion in comparison with other commonly used methods of accounting for Vs uncertainty

Forward modeling of Rayleigh surface waves for analytical characterization of dominant dispersion trends

A probabilistic investigation on the dynamic behaviour of pile foundations in homogeneous soils

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