Evaluating Proxy-Based Site Response in Israel

2020 ◽  
Vol 110 (6) ◽  
pp. 2953-2966
Author(s):  
Almog Baram ◽  
Gony Yagoda-Biran ◽  
Ronnie Kamai
Keyword(s):  
Site Response ◽  
Model Performance ◽  
Velocity Profiles ◽  
Large Database ◽  
Response Models ◽  
Alternative Site ◽  
Depth Effects

ABSTRACT Three alternative site-response models are developed, using two complementing predictors, accounting for both stiffness and depth effects. The analysis is based on a large database of velocity profiles and their associated calculated amplifications with respect to the local generic rock profile. The frequency of peak amplification—fpeak—is chosen to supplement VS30, after considering the predictability of eight different site proxies. The suggested models are continuous in terms of spectral periods as well as in terms of their predictor parameters—VS30 and fpeak. Model performance is evaluated in terms of the reduction in variability. For example, for a spectral period of T=0.5  s, using either one of the suggested models reduces the amplification variability from 0.4 to 0.18, whereas using VS30 alone reduces it only to 0.24. This improvement suggests that the addition of fpeak is a significant improvement in the midperiod range.

Taiwan-Specific Model for VS30 Prediction Considering Between-Proxy Correlations

2018 ◽  
Vol 34 (4) ◽  
pp. 1973-1993 ◽  
Author(s):  
On Lei Annie Kwok ◽  
Jonathan P. Stewart ◽  
Dong Youp Kwak ◽  
Pang-Li Sun
Keyword(s):  
Ground Motion ◽  
Prediction Models ◽  
Site Response ◽  
Specific Model ◽  
Weighted Mean ◽  
Response Models ◽  
Database File ◽  
A Site ◽  
Gradient Effects ◽  
Model Weighting

Ergodic site response models are generally conditional on the time-averaged shear wave velocity in the upper 30 m ( V S30). Ground motion databases contain many recordings from Taiwan, and because of site characterization efforts, 56% of recording sites have V S30 derived from measurements. We develop proxy-based V S30 prediction models, one application of which is for the remaining 44% of Taiwan sites. Our approach, which can be suitable for other regions, differs from previous studies in which proxies are based on detailed geologic categories and possible within-category topographic gradient effects. Instead, we use three broad, age-based geologic categories, and for the youngest category of Holocene and Quaternary undivided sediments, we propose models conditioned on gradient and elevation. We also adapt a geomorphic terrain-based method, thus providing two V S30-prediction models. We describe a model weighting scheme that combines the models in consideration of their relative dispersions and correlation, producing a weighted mean and standard deviation natural-log V S30. Included as an electronic supplement is a profile database file and a site database with site parameters for Taiwan ground motion stations.

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

GeoRisk 2011 ◽  
2011 ◽  
Author(s):  
E. M. Thompson ◽  
L. G. Baise ◽  
Robert E. Kayen ◽  
Eugene C. Morgan ◽  
James Kaklamanos
Keyword(s):  
Site Response ◽  
Explanatory Variables ◽  
Alternative Site

Mapping Fundamental-Mode Site Periods and Amplifications from Thick Sediments: An Example from the Jackson Purchase Region of Western Kentucky, Central United States

2021 ◽  
Author(s):  
Yichuan Zhu ◽  
Zhenming Wang ◽  
N. Seth Carpenter ◽  
Edward W. Woolery ◽  
William C. Haneberg
Keyword(s):  
Shear Wave ◽  
Wave Velocity ◽  
Shear Wave Velocity ◽  
Fundamental Mode ◽  
Site Response ◽  
Velocity Profiles ◽  
Wave Velocities ◽  
Shear Wave Velocities ◽  
Jackson Purchase ◽  
Western Kentucky

ABSTRACT V S 30 is currently used as a key proxy to parameterize site response in engineering design and other applications. However, it has been found that VS30 is not an appropriate proxy, because it does not reliably correlate with site response. Therefore, the VS30-based National Earthquake Hazards Reduction Program site maps may not capture regional site responses. In earthquake engineering, site resonance, which can be characterized by the fundamental mode with a site period (Tf) and its associated peak amplification (A0), is the primary site-response concern. Mapping Tf and A0 is thus essential for accurate regional seismic hazard assessment. We developed a 3D shear-wave velocity model for the Jackson Purchase Region of western Kentucky, based on shear-wave velocity profiles interpreted from seismic reflections and refractions, mapped geologic units, and digital-elevation-model datasets. We generated shear-wave velocity profiles at grid points with 500 m spacing from the 3D model and performed 1D linear site-response analyses to obtain Tf and A0, which we then used to construct contour maps for the study area. Our results show that Tf and A0 maps correlate with the characteristics of regional geology in terms of sediment thicknesses and their average shear-wave velocities. We also observed a strong dependency of A0 on bedrock shear-wave velocities. The mapped Tf and A0 are consistent with those estimated from borehole transfer functions and horizontal-to-vertical spectral ratio analyses at broadband and strong-motion stations in the study area. Our analyses also demonstrate that the depth to bedrock (Zb) is correlated to Tf, and the average sediment shear-wave velocity (VS-avg) is correlated to A0. This implies that Zb and VS-avg may be considered as paired proxies to parameterize site resonance in the linear-elastic regime.

Nonlinear shear stress reduction factor (rd) for assessment of liquefaction potential in Christchurch Central Business District

2014 ◽  
Vol 47 (1) ◽  
pp. 1-14
Author(s):  
James N. Dismuke
Keyword(s):  
Shear Stress ◽  
Stress Reduction ◽  
Site Response ◽  
Ground Motions ◽  
Limit State ◽  
Central Business District ◽  
Reduction Factor ◽  
Response Models ◽  
Business District ◽  
Nonlinear Shear

Simplified procedures for evaluating liquefaction triggering potential use the nonlinear shear stress reduction factor, rd, to estimate the peak earthquake-induced cyclic shear stress within the soil strata. Previous studies have derived rd by considering the response of representative ground profiles subjected to input ground motions with a range of ground motion characteristics. In this study, site–specific rd for serviceability limit state (SLS) and ultimate limit state (ULS) design ground motions are developed using site response models of the Christchurch Central Business District (CBD). The site response models are generated for typical geologic conditions of Christchurch CBD with shear wave velocity, Vs, profiles developed from the results of multichannel analysis of surface waves (MASW) surveys conducted across Christchurch CBD. A total of 528 simulations were conducted using 1D nonlinear time domain site response analyses using a suite of input ground motions that are representative of controlling ground motion scenarios for seismic hazard of Christchurch. The results of the ground response analyses are used to determine Christchurch CBD-specific rd relationships for liquefaction triggering assessments. The proposed relationships provide a better estimate of the cyclic stress ratios induced below Christchurch CBD when subjected to design SLS and ULS ground motions as compared to typical practice using generic liquefaction assessment methodologies.

scholarly journals Site Effects in Structural Response Predictions of Inelastic SDOF Oscillators

2012 ◽  
Vol 28 (3) ◽  
pp. 859-883 ◽  
Author(s):  
Dominic Assimaki ◽  
Wei Li ◽  
Michalis Fragiadakis
Keyword(s):  
Ground Motion ◽  
Site Response ◽  
Structural Response ◽  
Attenuation Relations ◽  
Period Range ◽  
Response Models ◽  
Linear Elastic ◽  
Ground Motion Variability ◽  
Inelastic Displacement Ratio ◽  
Input Motion

We study how the inelastic structural response predicted via synthetic seismograms is affected by the selection of site response models in ground motion simulations. We first generate synthetics for multiple scenarios and site conditions in Southern California using attenuation relations, site specific linear, vis-coelastic and nonlinear analyses, and estimate the ground motion variability that results from the soil model selection. We next use bilinear single degree-of-freedom oscillators to demonstrate how this variability propagates to the inelastic structural response predictions. Results show high bias and scatter of the inelastic displacement ratio predicted using the empirical and linear elastic site response models relative to the nonlinear, for periods close to the fundamental period of the site. For the synthetic motions and sites used, we derive empirical correlations between the amount of bias and period range where it manifests, and selected input motion and site parameters.

scholarly journals Conversion Uplift in E-Commerce: A Systematic Benchmark of Modeling Strategies

2019 ◽  
Vol 18 (03) ◽  
pp. 747-791 ◽  
Author(s):  
Robin Gubela ◽  
Artem Bequé ◽  
Stefan Lessmann ◽  
Fabian Gebert
Keyword(s):  
Machine Learning ◽  
Learning Algorithm ◽  
Model Performance ◽  
Predictive Performance ◽  
Academic Disciplines ◽  
Response Models ◽  
Uplift Modeling ◽  
Online Retailers ◽  
Using Data ◽  
Modeling Strategy

Uplift modeling combines machine learning and experimental strategies to estimate the differential effect of a treatment on individuals’ behavior. The paper considers uplift models in the scope of marketing campaign targeting. Literature on uplift modeling strategies is fragmented across academic disciplines and lacks an overarching empirical comparison. Using data from online retailers, we fill this gap and contribute to literature through consolidating prior work on uplift modeling and systematically comparing the predictive performance and utility of available uplift modeling strategies. Our empirical study includes three experiments in which we examine the interaction between an uplift modeling strategy and the underlying machine learning algorithm to implement the strategy, quantify model performance in terms of business value and demonstrate the advantages of uplift models over response models, which are widely used in marketing. The results facilitate making specific recommendations how to deploy uplift models in e-commerce applications.

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