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 presented.), a site term (Formula presented.) with standard deviation (Formula presented.), and a event- and site-specific remaining residual (Formula presented.) with standard deviation (Formula presented.). Values for (Formula presented.) and (Formula presented.) 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.

One-dimensional site response analysis (1D SRA) remains the state of practice to estimate site-specific seismic response, despite the ample evidence of discrepancies between observations and 1D SRA-based predictions. These discrepancies are due to errors in the input parameters, intrinsic limitations in the predicting capabilities of 1D SRAs even for sites relatively compliant with the 1D SRA assumptions, and the inability of 1D SRAs to model three-dimensional (3D) wave propagation phenomena. This article aims at reducing 1D SRA mispredictions using small-strain damping profiles factored by a damping multiplier (Dmul) and randomized shear-wave velocity (VS) profiles. An approach for conducting 1D SRAs for site-specific site response assessment is developed to reduce the 1D SRA errors in magnitude and variability. First, sites from a database of 534 downhole sites are classified as 1D- or 3D-like, depending on the substructure conditions inferred from observed transfer functions. Second, data from the 1D-like sites are compared against predictions from 1D SRAs conducted using various trials of Dmul and VS standard deviations (Formula presented.) for VS randomization. Third, Dmul and (Formula presented.) are selected based on their combined ability to reduce the root mean square error (RMSE) in SRA predictions. Results indicate that 1D SRAs conducted with Dmul = 3 and (Formula presented.) lead to an overall minimum RMSE and thus provide more accurate site response estimates. The use of these parameters in forward SRA predictions is discussed in a companion paper.

The seismic performance of Balboa Boulevard during the 1994 MW 6.7 Northridge earthquake was examined through nonlinear deformation analyses (NDAs) using advanced tools to (1) investigate the failure mechanism leading to ground deformations at this site; (2) evaluate the accuracy of the adopted analysis methods, engineering procedures, and state-of-the-art tools to reasonably estimate horizontal ground displacements; and (3) identify key factors and parameters contributing to earthquake-induced ground deformations at this site. One-dimensional (1D) liquefaction vulnerability indexes (LVIs) and permanent displacements using Newmark sliding block analyses were also estimated and compared against ground deformations observed after the earthquake. The geotechnical characterization of Balboa Boulevard was assessed based on field and laboratory data obtained from two investigation campaigns. Transitional probability geostatistics were used to develop stratigraphic models that capture the heterogeneity and the spatial variability patterns of sand-like and clay-like soils present at this site. The stratigraphic models were implemented in the finite difference software FLAC and the behavior of sand-like and clay-like soils simulated using the PM4Sand and PM4Silt constitutive models, respectively. Sensitivity analyses were performed to address uncertainties associated with the spatial variability of soils, input ground motions, the proportion of sand-like and clay-like soils within the soil deposit, and the strength properties of these materials. Results from NDAs suggest that a compounded effect of both liquefaction of sand-like soils and cyclic softening of clay-like soils led to the excessive ground deformations at Balboa Boulevard. This study sheds light on the importance of using appropriate engineering procedures and numerical modeling protocols in the prediction of deformation patterns, the selection of key input parameters, as well as the applicability of LVIs in complex sites.

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.

Numerical simulations of centrifuge experiments examining a sheet-pile wall with a liquefiable backfill are conducted and results are compared against the experimental responses to evaluate the numerical tools’ ability to accurately predict the seismic performance of this geosystem. The platform FLAC and the constitutive model PM4Sand are used for the simulations, and focus is placed on the sheet-pile wall displacements. The influence of relative density (DR) on the system's response is evaluated, together with the influence of other parameters such as the soil's permeability and numerical model construction method. The consideration of both mass-based and CPT-based DR estimates allows for a better prediction of the overall range of permanent sheet-pile wall displacements. Other parameters have a moderate to important effect on the estimated pre-shaking displacements but only a minor to moderate effect on the end-of-shaking wall displacements.

We present an application programming interface (API) which facilitates public access to a global relational database of earthquake ground motion intensity measures, associated metadata, and time-series data. Next Generation Attenuation (NGA)-East and NGA-West2 project spreadsheets have been adapted into a relational database format composed of multiple tables through a series of primary and foreign keys. The combined dataset has been expanded to include contributions from earthquakes, generally with magnitudes greater than M3.9, that have occurred since the conclusion of the data synthesis component of both projects in 2011. Currently the database includes 62,449 ground motions recorded at 9,092 stations for 899 events. The database is accessible through an API, which allows users to interact with and query the database directly without detailed knowledge of structure query language (SQL). Simple queries are constructed by appending relatively straightforward query string parameters to the end of a uniform resource location (URL) that serves as an endpoint, which returns only data that satisfy the query constraints. The web-served nature of the database means that users have immediate access to ground motion data as soon as it is collected, reviewed, and uploaded. Furthermore, integrated end-to-end workflows – which do not require files to be downloaded and saved in local memory – are possible through the API. The structure of the database has been designed to accommodate growth, with ongoing efforts to integrate global ground motion data in anticipation of the NGA-West3 project, and improve ease-of access through the API.