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In this paper, efforts to characterize and compare the full-scale in situ three-dimensional (3D) dynamic response of a low-plasticity silt deposit to multidirectional loading from two different sources, a vibroseis shaker named T-Rex and controlled blasting, are presented. Horizontal vibroseis shaking at a frequency, f , of 10 Hz, produced dynamic responses in the silt that ranged from linear-elastic to nonlinear-inelastic, inducing maximum equivalent direct simple shear (DSS) shear strains, γDSS,max , up to 0.15% and residual excess pore pressure ratios, ru,r , of 14.1%. Blast-induced shear waves with predominant frequencies ranging from 9.6 to 14.6 Hz excited nonlinear-elastic and nonlinear-inelastic responses in the silt deposit, with γDSS,max of 1.14% and maximum ru,r of 61%. Importantly, these responses were observed to be minimally influenced by high frequency compression waves. Multidirectional loading, and excess pore pressure, ue , migration and impedance were identified as the predominant factors for achieving the large ru,r in the silt deposit from these two in situ testing techniques. The cyclic threshold shear strain, γtp , to trigger ru,r observed from the T-Rex shaking equaled 0.007% to 0.011% and varied with the initial soil stiffness. The two testing techniques demonstrated that the in-situ shear modulus, G , reduced to 90% of the maximum shear modulus, Gmax , at γDSS,max≈γtp , whereas by γDSS,max≈1% , G further reduced to 10 to 30% of Gmax corresponding to ru,r of ∼60%. Changes in soil fabric were quantified using small-strain shear-wave velocity measurements performed before and/or upon initiation and after each stage of dynamic testing, and were linked to the observed increase and decrease in γtp for the shallower and deeper 3D elements, respectively, following T-Rex shaking. The side-by-side comparison of the dynamic responses and soil properties derived from these two distinctly different field-testing techniques validate the use of controlled blasting for quantifying in situ dynamic soil properties and responses. [ABSTRACT FROM AUTHOR]

Surface wave testing is a powerful tool for noninvasive seismic site characterization. It includes a wide variety of active-source and passive-wavefield methods [e.g., spectral analysis of surface waves (SASW), multichannel analysis of surface waves (MASW), microtremor array measurements (MAM)] that can be applied to many different field conditions. The dispersion data collected with all these methods can be inverted to produce (one-dimensional) 1D shear wave velocity (VS) profiles of the subsurface. A critical part of this inversion procedure is the need to develop several trial model parameterizations with different numbers of layers as a means for investigating epistemic uncertainty and nonuniqueness when attempting to fit the experimental dispersion data. This is especially important when a priori information either is not available or does not extend to great enough depths to constrain the inversions. These trial parameterizations are used to vary the number of potential layers present in the subsurface models and to set the acceptable search ranges for depths to boundaries and stiffness in each layer. The inversion results are highly affected by the parameterizations. When performing high-quality inversions, it is important to use different parameterization options to fully explore potential conditions at the site and characterize the epistemic uncertainty of the inversion process. While this practice allows for a robust analysis of the experimental dispersion data and its uncertainty, it also generates many potential subsurface models for the site, which can represent a challenge for engineers when deciding which VS profiles best represent the true subsurface layering for use in subsequent analysis and design (e.g., seismic site response). This paper presents an approach, called the DeltaVs method, for systematically evaluating the depths of layer boundaries across all acceptable models determined from several different inversion layering parameterizations as a means to identify distinct clusters of boundaries. Using these clusters, the number and location of meaningful layer boundaries can be determined for many sites, thereby allowing for the elimination of some parameterization options containing more, or fewer, boundaries and a reduction in epistemic uncertainty. The distributions of layer boundaries within these clusters can then be used to determine statistics for the depths of layer boundaries that are consistent with the epistemic uncertainty of the models produced by the inversion procedure. The DeltaVs method is demonstrated on 12 synthetic ground models as well as one field data set. [ABSTRACT FROM AUTHOR]

Site-specific subsurface conditions are known to significantly influence the frequency content and amplitude of seismic ground shaking. When attempting to model these effects, known as seismic site effects, most studies have focused on the importance of vertically characterizing subsurface geomaterials. However, laterally characterizing the geomaterials' variability has generally either been overlooked or oversimplified. As such, little is actually known about the spatial area that influences seismic site response. In this article, we discuss insights that have been gained regarding the spatial area that influences site response from performing two-dimensional (2D) ground response analyses (GRAs) for the Treasure Island Downhole Array (TIDA) site. In these numerical analyses, we use a site-specific, large-scale, three-dimensional (3D) shear wave velocity (Vs) model that has been developed to a depth of 150 m over the entirety of Treasure Island (an area of approximately 1.6×1.0 km2). We investigate the lateral extent influencing site response and its azimuthal variability using: (1) four cross sections with increasing lateral extent along the same azimuth; and (2) 12 cross sections with different azimuths that uniformly sample the full 3D Vs model. By comparing 2D GRA predictions to recorded earthquake ground motions at TIDA, we systematically highlight the large spatial area that influences site response, which extends to distances as much as 1 km from the TIDA sensors. Although the TIDA site is often assumed to be archetype of one-dimensional (1D) site conditions, our findings support the idea that there may not be many truly 1D sites due to the large spatial area that influences site response. While some sites can be reasonably modeled using 1D GRAs, moving the engineering profession forward requires focusing our efforts on developing site-specific subsurface models over larger areas to better understand and accurately model seismic site response. [ABSTRACT FROM AUTHOR]

A significant amount of seismic site response research over the past decade has focused on our abilities to replicate recorded ground motions at borehole array sites, where both the input (rock) and output (surface) ground motions are known. When viewed in aggregate, these studies have found that approximately 50% of borehole array sites are poorly modeled using one-dimensional (1D) ground response analyses (GRAs) based on a single shear wave velocity (Vs) profile, with individual studies reporting values between approximately 30%–80%. While there is no doubt that some sites are indeed too variable to be modeled using 1D GRAs, it is possible that simple 1D analyses could still be effectively used at many sites if spatial variability is accounted for via a rational, site-specific approach. In this study, we investigate five alternative approaches that can be used to account for spatial variability in 1D GRAs: (1) Vs randomization, (2) shear wave travel time randomization, (3) utilization of Vs suites derived from surface wave testing covering a large area, (4) incorporation of a pseudo-3D Vs model derived from a horizontal-to-vertical spectral ratio geostatistical approach, and (5) damping modifications. These approaches are investigated at two US borehole array sites (the Treasure Island and Delaney Park Downhole Arrays) so that the GRA results can be compared with recorded small-strain ground motions. Spatial variability is accounted for by generating approximately 250 Vs profiles for each approach, except for damping modifications, wherein only a single Vs profile is used, but with increased damping to account for wave scattering originating from spatial discontinuities. Through qualitative and quantitative comparisons, we assess the relative and absolute effectiveness of each approach, highlight their limitations, and propose potential improvements that can help overcome these limitations in practice. [ABSTRACT FROM AUTHOR]

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, surfacewave 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 Vs profiles such as the median, bounding-type, and randomly generated Vs profiles for each site were compared with the experimentally measured dispersion data. It was found that the theoretical dispersion curve from the median Vs profile provided a satisfactory fit to the experimental data, but the theoretical dispersion curves from bounding-type Vs profiles did not. Furthermore, randomly generated Vs profiles resulted in some theoretical dispersion curves that fit the experimental data and many that did not. The authors recommend comparing theoretical dispersion curves for candidate Vs profiles and layered earth models with the measured dispersion data at a site prior to using the candidate profiles to account for uncertainty in site response analyses as a quantitative way to judge if the Vs profiles represent realistic site conditions. [ABSTRACT FROM AUTHOR]

Uncertainty in site response analyses can be attributed to a number of parameters, including analysis methods, input ground motions, nonlinear dynamic soil properties, and shear-wave velocity profiles. In this paper, several approaches commonly used to account for shear-wave velocity (Vs) uncertainty in site response are investigated. Specifically, the Vs profiles considered are categorized into three groups: (1) Vs profiles determined directly from surface-wave inversion, (2) simple statistical Vs profiles derived indirectly from the surface-wave Vs profiles (including bounding-type, median, and other percentile Vs profiles), and (3) statistically based, randomly generated Vs profiles. A companion paper discusses the development of these Vs profiles for two international blind-study sites. In this paper, the effects of using each approach to account for Vs uncertainty in site response are investigated by linking the dispersion misfit values for each Vs profile to variability in equivalent linear site response estimates. Clear trends exist between variability in site response estimates and dispersion misfit values at both sites. Thus, the experimental dispersion data can be used to help select suites of Vs profiles, generated either directly from inversion or through a randomization model, that account for uncertainty in a meaningful way without including unrealistic statistical profiles that result in too much site response variability. [ABSTRACT FROM AUTHOR]

Relationships between seismic site classification and surficial geology for the city of Fairbanks, Alaska, for both frozen (winter) and unfrozen (summer) surface conditions are investigated in this article. The work is based on 59 shear wave velocity () profiles collected using the spectral analysis of surface waves (SASW) method. Forty-three profiles were collected during the summer when the ground surface was fully thawed, and 16 profiles were collected by reoccupying some of the test locations during fully frozen winter ground surface conditions. Relationships between mean over the top 30 m of the subsurface () and surficial geologic units in Fairbanks were developed, permitting estimates of seismic site classification throughout the city for both frozen and unfrozen conditions. Much of Fairbanks was determined to have been founded on NEHRP Site Class D material when unfrozen. When frozen, the of the near-surface material increased significantly (by 700% on average). However, this drastic increase in stiffness was typically limited to the top 1 to 2 m of the subsurface and only resulted in an increase in site class from NEHRP D to NEHRP C at three of the 16 sites retested during the winter. [ABSTRACT FROM AUTHOR]

The refraction microtremor (ReMi) method uses a linear array of receivers to record passive noise stress waves, thereby negating the need for a strong active source such as those typically employed in other linear-array surface-wave methods. The simplicity of such an approach is very appealing; however, there is a potential for significant uncertainty in shear-wave velocity (Vs) estimates obtained in this manner because much is unknown about the seismic wavefield that is being sampled. This article examines intramethod variability in ReMi dispersion measurements and Vs estimates at shallow bedrock sites. The focus is not on evaluating whether ReMi measurements yielded the 'true' Vs profiles for the study sites, but rather on evaluating how the dispersion curves and Vs profiles at the sites were affected by variations in the seismic wavefield sampled by a linear array of receivers. It was found that changes in the sampled seismic wavefield, obtained through employing various array orientations at a site and inclusion of actively generated noise, resulted in significant variations in the ReMi-obtained dispersion curves and Vs profiles at the study sites, thus yielding a high level of intramethod variability for a given test location. [ABSTRACT FROM AUTHOR]