Conducting 1D site response analyses to capture 2D V_S spatial variability effects

Abstract

One-dimensional site response analyses (1D SRAs) with shear-wave velocity ( VS) randomization are commonly performed to estimate median site-specific amplification factors (AFs) under the implicit assumption that this approach yields a realistic response. In this work, an investigation is conducted to determine the appropriate amount of VS randomization (σlnVs) needed to capture a median response that accounts for 2D VS spatial variability effects. Results from 2D SRAs and 1D SRAs with VS randomization show that the median 2D seismic responses are generally higher than 1D responses at the site’s fundamental frequency, and that higher VS variability has a mild impact on the median 2D seismic response amplitude at the fundamental frequency, whereas it significantly reduces the median 1D response. Findings indicate that the 84th percentile AFs based on 1D SRAs conducted with VS randomization using σlnVs = 0.25, approximate well with the more realistic median 2D SRA-based AFs around the fundamental frequency, while the 70th to 60th percentiles might be more appropriate at higher frequencies. The benefit of using percentiles of the 1D SRA-based AFs higher than the median is shown for different site conditions and supported by comparisons against empirical data from four downhole sites.

A borehole array data–based approach for conducting 1D site response analyses I: Damping and VS randomization

“…A D mul = 3 is consistent with results by Tao and Rathje (2019), who estimated D mul based on the variation of measured values of k at borehole array sites. A s ln V S = 0:2 À 0:3 is consistent with findings by Pretell et al (2022a), who compared results from 2D SRAs and 1D SRAs with V S randomization to identify the most appropriate s ln V S to capture the effects of V S spatial variability of soils on the site response.…”

“…To achieve these goals, this study builds off the work by Tao and Rathje (2019) and Pretell et al (2022a) to find the most appropriate D mul and σ ln V S by comparing 1D SRA predictions to ground motion data from 1D-like borehole array sites, whose intrinsic errors in 1D SRAs are more clearly identified. Pretell et al (2022a) hypothesized that V S randomization can be treated as a multi-purpose tool used to capture site-specific features affecting the seismic response such as (1) V S spatial variability (e.g. Assimaki et al, 2003; de la Torre et al, 2021; El Haber et al, 2019; Nour et al, 2003; Pretell et al, 2022a); (2) a dipping bedrock and topography (e.g.…”

“…Griffiths et al, 2016b;Passeri et al, 2020;Stewart et al, 2014;Tao and Rathje, 2019;Teague et al, 2018). Pretell et al (2022a) show that not only s ln V S is generally too high, but site response underpredictions also originate from considering the median site response as representative. Based on a numerical investigation, Pretell et al (2022a) suggest that the 84 th percentile site response from 1D SRAs conducted with randomized V S profiles (s ln V S = 0:25) is an appropriate response that accounts for V S spatial variability at the site's fundamental frequency.…”

“…The second part consists of the quantification of the 1D SRA remaining errors such that they can be considered in forward site response predictions. This article focuses on the first part, and the companion paper (Pretell et al, 2023) describes the second part.…”

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

“…More generally, V S randomization can be calibrated to capture the effect of site-specific features affecting site response for different purposes, such as to capture V S variability or edge effects (e.g. Pretell et al, 2022). In this article, V S randomization is used to reduce modeling errors.…”