Surface-wave site characterization at 52 strong-motion recording stations affected by the Parkfield, California, M6.0 earthquake of 28 September 2004

Thompson, Eric M.; Kayen, Robert E.; Carkin, Brad; Tanaka, Hajime

doi:10.3133/ofr20101168

Cited by 5 publications

(5 citation statements)

References 4 publications

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“…Kaklamanos et al, 2020;Passeri et al, 2019), only sites with a measured V S profile are used. The measured V S profiles from Japan are provided on the KiK-net database website, whereas various sources are used for the V S profiles of sites in the United States (Afshari et al, 2019;Gibbs et al, 2000;Holzer and Youd, 2007;Thompson et al, 2010;Thornley et al, 2019). A compromise is made to include a few sites with gaps in the V S profile, typically at the top 1-2 m (e.g.…”

Section: Site Characterizationmentioning

confidence: 99%

A borehole array data–based approach for conducting 1D site response analyses II: Accounting for modeling errors

2023

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Site response estimates from one-dimensional (1D) site response analyses (SRAs) carry inaccuracies due to modeling and parametric errors. Modeling errors are due to the condensation of the three-dimensional (3D) wave propagation phenomenon to the vertical propagation of a horizontally polarized wave through a soil column, and parametric errors are due to the incomplete knowledge of the distributions of soil parameters, leading to the selection of nonoptimal input parameters for a site of interest. While parametric errors are traditionally handled using different soil parameters (e.g. alternative shear-wave velocity profiles), modeling errors are generally neglected. This paper proposes an approach for conducting linear elastic 1D SRAs to improve site response predictions and account for modeling errors. First, ground-motion data from borehole array sites are collected, processed, and screened for appropriateness (e.g. expected shear strains lower than 0.01%, signal-to-noise ratio higher than 3). Second, 1D SRA predictions in terms of transfer functions and amplification factors are compared against observations, and the discrepancies are quantified as residuals. Finally, the residuals are partitioned into a model bias term [Formula: see text], a site term [Formula: see text] with standard deviation [Formula: see text], and a event- and site-specific remaining residual [Formula: see text] with standard deviation [Formula: see text]. Values for [Formula: see text] and [Formula: see text] for forward predictions are recommended. The sensitivity of the site response residuals to region, site type (1D- or 3D-like), and the applicability of findings to outcropping applications are discussed, and an example application for a hypothetical project site is presented.

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Section: Site Characterizationmentioning

confidence: 99%

A borehole array data–based approach for conducting 1D site response analyses II: Accounting for modeling errors

2023

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“…The friction angle of the soil is estimated at 40 degrees, and the unit weight of the soil was estimated at 19 kN/m 3 . The shear wave velocity profile is documented in Thompson et al 19 . The foundations for the baseline archetypes (although their foundations were not modeled) and stiff soil archetypes were designed for an allowable bearing pressure of 144 kPa, while the soft soil archetypes were designed for an allowable bearing pressure of 72 kPa.…”

Section: Building Archetypes and Designsmentioning

confidence: 99%

Factors affecting the seismic collapse performance of realistic low‐rise braced frame buildings, including soil structure interaction and foundation flexibility

Wichman

Berman

Lehman

et al. 2022

Earthq Engng Struct Dyn

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Previous computational studies of short-period buildings have shown increasing collapse probabilities with decreasing building period; a trend that has not been observed in past earthquakes. In this study, collapse performances of twelve short-period steel special concentrically braced frame (SCBF) building archetypes were examined using dynamic analysis and the methods described in FEMA P-695 to investigate this gap between analytically predicted and historically observed collapse rates. The archetypes varied key design and modeling parameters that could influence the behavior. These parameters included number of stories, level of design seismicity, redundancy, the inclusion of soil-structure interaction (SSI) and foundation flexibility, and the removal of reserve moment frame resistance in modeling. Practicing engineers designed the archetypes resulting in realistic designs, including overstrength values representative of this building type. The calculated overstrength values were much higher than those found in previous studies, largely a result of the archetype building layouts, brace width-to-thickness ratio limitations, and the large differences between tension and compressive brace strength that occur when design demands are low. The higher overstrength values found in this study resulted in lower probabilities of collapse, relative to previous collapse studies and showed that probabilities of collapse decreased with decreasing period. Additionally, the probability of collapse increased significantly for the nonredundant archetype, but changed insignificantly for the archetype without reserve moment frame capacity. Inclusion of SSI and foundation flexibility resulted in a complete change in behavior where braces remained elastic and the braced frames rocked on their foundations, resulting in decreased collapse probabilities.

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“…The 52 velocity profiles collected by Thompson et al (2010) at strong motion stations are shown in Figure 1. Additionally, we show the epicenter of the 2004 M 6.0 Parkfield earthquake, but we do not include the records from this earthquake in our analysis to avoid the complication of nonlinear and finite fault effects which could be important because epicentral distance to these stations is so small.…”

Section: Data Velocity Profiles and Ground Motion Selectionmentioning

confidence: 99%

“…Of the 52 stations with measured velocity profiles in the Parkfield region, 36 recorded the Coalinga earthquake. Figure 1 also shows the Jennings (1958) Thompson et al (2010) employed the spectral analysis of surface waves (SASW), and so we refer to the V S30 estimated from an SASW V S profile as SASW S V 30 . Additionally, we compute the fundamental site frequency (f 0 ) using the procedure described by Zhao et al, (2006).…”

Section: Data Velocity Profiles and Ground Motion Selectionmentioning

confidence: 99%

“…We refer to the magnitude of the topographic slope computed using the Wald and Allen method as δ and the estimates of V S30 as δ 30 S V . Thompson et al (2010) collected 52 noninvasive velocity profiles at strong motion station in the Parkfield region of California. These data provide a valuable opportunity to assess the accuracy of different site response explanatory variables because these densely spaced velocity profiles are generally associated with strong motion stations.…”

Section: Introductionmentioning

confidence: 99%

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A Case Study of Alternative Site Response Explanatory Variables in Parkfield, California

et al. 2011

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The combination of densely-spaced strong-motion stations in Parkfield, California, and spectral analysis of surface waves (SASW) profiles provides an ideal dataset for assessing the accuracy of different site response explanatory variables. We judge accuracy in terms of spatial coverage and correlation with observations. The performance of the alternative models is period-dependent, but generally we observe that: (1) where a profile is available, the square-root-of-impedance method outperforms V S30 (average S-wave velocity to 30 m depth), and (2) where a profile is unavailable, the topographic-slope method outperforms surficial geology. The fundamental site frequency is a valuable site response explanatory variable, though less valuable than V S30 . However, given the expense and difficulty of obtaining reliable estimates of V S30 and the relative ease with which the fundamental site frequency can be computed, the fundamental site frequency may prove to be a valuable site response explanatory variable for many applications.

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Surface-wave site characterization at 52 strong-motion recording stations affected by the Parkfield, California, M6.0 earthquake of 28 September 2004

Cited by 5 publications

References 4 publications

A borehole array data–based approach for conducting 1D site response analyses II: Accounting for modeling errors

A borehole array data–based approach for conducting 1D site response analyses II: Accounting for modeling errors

Factors affecting the seismic collapse performance of realistic low‐rise braced frame buildings, including soil structure interaction and foundation flexibility

A Case Study of Alternative Site Response Explanatory Variables in Parkfield, California

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