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This paper presents a model for distributing zones of liquefaction and nonliquefaction for use in regional liquefaction risk analysis. There are two broad methodologies that have been used to evaluate liquefaction risk on the regional scale: (a) application of site-specific procedures using soil properties inferred from geology, or (b) application of geospatial proxies for liquefaction. The first approach will tend to predict similar liquefaction probabilities across broad areas with similar geology, water table depths, and shaking intensities. The second approach yields the probability of liquefaction, which can be interpreted as the portion of the area affected by liquefaction ((Formula presented.)). Neither approach, however, gives an informed prediction of the spatial distribution of liquefaction and the resulting displacements, which are particularly important for assessments of seismic risk for spatially distributed infrastructure systems. We propose a methodology for incorporating spatial correlation into a geospatial proxy for liquefaction to create maps of liquefaction and nonliquefaction for a given earthquake scenario. First, we describe a latent Gaussian process that is assumed to govern the spatial distribution of liquefaction. Next, a database of empirical observations of liquefaction is used to obtain the coefficients that describe that latent Gaussian process. The proposed model yields random realizations of maps of liquefaction and nonliquefaction conditioned on a map of (Formula presented.). Such maps can be used to constrain the area over which displacements are estimated using soil properties inferred from geology and are therefore a critical component in reducing bias in assessments of liquefaction risk at the regional scale.

This paper presents an approach for estimating liquefaction-induced ground deformations on a regional scale in support of risk analyses of spatially distributed infrastructure systems. Logic trees are used to represent uncertainty in subsurface conditions (i.e., results from cone penetration testing and the water table depth) as well as uncertainty between models for liquefaction susceptibility, triggering, and deformations. Finally, a Gaussian process model is used to assign realistic spatial patterns of liquefaction-induced ground failure. The approach described here emphasizes the uncertainty in regional liquefaction risk analysis and takes measures to reduce the potential foroverestimation of this risk. The method was developed for application in analyzing the risk faced by spatially-distributed gas infrastructure in California.

Seismic risk for spatially distributed infrastructure is driven mainly by ground failure, defined as permanent ground displacements from mechanisms such as landslides, liquefaction, and seismic compression. Most forms of ground failure are a consequence of soil responses to ground shaking, which should be evaluated on a hazard-consistent scenario basis to represent spatial correlations of intensity measures. A companion paper describes a methodology for identifying hazard-consistent event scenarios. Seismic ground failure responses are evaluated based on regionally-accessible information on geology, groundwater hydrology, and terrain. Given these inputs, liquefaction and landslide displacements are predicted point-by-point on a 10 m grid using customized analysis procedures and logic trees for each ground failure type. For each point, these analyses provide probabilities that the hazard exists, probabilistic distributions (accounting for epistemic uncertainties) of related displacements, and displacement directions (azimuths). Series of points expected to move together (e.g., in a single lateral spread) are grouped into polygons. Ground failure features (landslides, lateral spreads) of varying sizes may occur within these polygons. The output of these analyses are feature locations, sizes, displacement amounts, and displacement azimuths, which can be applied in subsequent fragility and risk analysis of distributed infrastructure systems.

This paper presents a data-informed, probabilistic methodology employed to assess regional co-seismic landslide hazards in California, primarily by jointly analyzing geologic data and geotechnical properties of various geologic units and incorporating uncertainties in the prediction analyses. Geotechnical data from a borehole database, a California statewide geologic map, and judgment in consultation with local geologists/geotechnical engineers are integrated to estimate a range of plausible shear strength parameters and slope properties that represent the epistemic uncertainty in these parameters. A logic tree approach is implemented to account for the epistemic uncertainties in the input model parameters, as well as in empirical displacement models, that may influence the accuracy of the co-seismic landslide displacement predictions.

PREdiction of NOn-LINear soil behavior (PRENOLIN) is an international benchmark aiming to test multiple numerical simulation codes that are capable of predicting nonlinear seismic site response with various constitutive models. One of the objectives of this project is the assessment of the uncertainties associated with nonlinear simulation of 1D site effects. A first verification phase (i.e., comparison between numerical codes on simple idealistic cases) will be followed by a validation phase, comparing the predictions of such numerical estimations with actual strongmotion recordings obtained at well-known sites. The benchmark presently involves 21 teams and 23 different computational codes. We present here the main results of the verification phase dealing with simple cases. Three different idealized soil profiles were tested over a wide range of shear strains with different input motions and different boundary conditions at the sediment/bedrock interface. A first iteration focusing on the elastic and viscoelastic cases was proved to be useful to ensure a common understanding and to identify numerical issues before pursuing the nonlinear modeling. Besides minor mistakes in the implementation of input parameters and output units, the initial discrepancies between the numerical results can be attributed to (1) different understanding of the expression “input motion” in different communities, and (2) different implementations of material damping and possible numerical energy dissipation. The second round of computations thus allowed a convergence of all teams to the Haskell–Thomson analytical solution in elastic and viscoelastic cases. For nonlinear computations, we investigate the epistemic uncertainties related only to wave propagation modeling using different nonlinear constitutive models. Such epistemic uncertainties are shown to increase with the strain level and to reach values around 0.2 (log10 scale) for a peak ground acceleration of 5 m=s2 at the base of the soil column, which may be reduced by almost 50% when the various constitutive models used the same shear strength and damping implementation.

The technique referred as ray approximation treats wave propagation in a heterogeneous medium at the infinitely small wavelength limit. This classic simplification allows useful approximate analytical results to be obtained in cases where complete description of the waveform behaviour is virtually unattainable, hence its wide use in physics. In seismology, this approximation has been widely applied. This paper presents an application in one-dimensional site response (1DSR) analysis: it is used herein, first to explain and elucidate the generality of some previous observations as to the use of the harmonic mean of a shear-wave velocity profile to represent the global behaviour of a site; and second to partially settle an open question in 1DSR, namely 'What are the equivalent homogeneous properties that yield the same response, in terms of natural frequencies and resonance amplitude, for a given inhomogeneous site?', providing a few assumptions are met – chiefly, that excitations of sufficiently high frequency are considered. [ABSTRACT FROM AUTHOR]

We demonstrate the effects of soil-structure interaction (SSI) for three idealized building typologies on a regional scale, using a simulated earthquake scenario of the 2008 MW 5.4 Chino Hills mainshock in southern California as an example. All the three buildings lie on shallow foundations, and they are subject to three-component simulated ground motions. To carry out this task, we develop a reduced order model (ROM) for each building typology that accounts for the effects of SSI on the building system in the time domain. We specifically use ensemble Kalman inversion (EnKI) to extract the soil impedance values from fully coupled soil-foundation-structure interaction simulations; and we interpolate the EnKI results to derive analytical functions that span the range of applicability of the soil impedance model. We then verify our ROMs by comparing results to fully coupled soil-foundation-structure interaction simulations, also known as direct modeling methods. We finally populate the simulation grid across southern California with the verified building ROMs, and interpret the responses in the form of maps that represent urban-scale effects of SSI on the seismic demand parameters such as maximum displacement, acceleration, and interstory drift. We also identify areas where the effects of SSI, given the resonant characteristics of a specific building, the foundation typology, and the local site conditions, lead to higher seismic demand relative to the fixed-base response. [ABSTRACT FROM AUTHOR]

In the fields of structural and geotechnical engineering, improving the understanding of soil–structure interaction (SSI) effects is critical for earthquake-resistant design. Engineers and practitioners often resort to finite element (FE) software to advance this objective. Unfortunately, the availability of software equipped with boundary representation for absorbing scattered waves and ensuring consistent input ground motion prescriptions, which is necessary for accurately representing SSI effects, is currently limited. To address such limitations, the authors developed Seismo-VLAB (SVL v1.0-stable) an open-source software designed to perform SSI simulations. The methodology considers the integration of advanced techniques, including the domain decomposition method (DDM), perfectly matched layers (PMLs), and domain reduction method (DRM), in addition to parallel computing capabilities to accelerate the solution of large-scale problems. In this work, the authors provide a detailed description of the implementation for addressing SSI modeling, validate some of the SVL's features needed for such purpose, and demonstrate that the coupled DRM–PML technique is a necessary condition for accurately solving SSI problems. It is expected that SVL provides a significant contribution to the SSI research community, offering a self-contained and versatile alternative. The software's practical application in analyzing SSI and directionality effects on 3D structures under seismic loading demonstrates its capability to model real-world earthquake responses in structural engineering. [ABSTRACT FROM AUTHOR]

The compression wave velocity (Vp) of sediments plays a key role in seismic wave amplification of vertical motion and is required in site response analysis. However, such information is usually lacking during field exploration (e.g. the surface wave method) because only shear wave velocity (Vs) is obtained. This aim of this study is to predict Vp based on Vs empirically and theoretically, particularly focusing on saturated conditions. The empirical approach is to establish the Vp correlation dependency on Poisson's ratio and Vs, and the theoretical approach is based on poroelastic theory that accounts for the interaction between fluid and soil skeleton. The engineering geological database for the Taiwan strong motion instrumentation program and the Kiban Kyoshin network database in Japan are adopted to establish an empirical model and validate poroelastic theory. The validated poroelastic approach is used to develop a constrained modulus reduction curve dependency on the porosity, Vs, Poisson's ratio and degree of saturation with a shear modulus reduction curve. The proposed approach can be used to develop generic Vp profiles and constrained modulus reduction curves for the site response to vertical motion given a site-specific Vs profile. [ABSTRACT FROM AUTHOR]