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Abstract: The purpose of this dissertation is to improve our understanding of uncertainty in earthquake site response models, using data from the Kiban-Kyoshin network (KiK-net) of vertical seismometer arrays in Japan. Site response models, which are used to estimate the ground motion at the surface of a site (as a function of the soil profile and the input ground motion), are associated with larg... read moree uncertainties and have often been found to poorly replicate observed ground motions. Vertical seismometer arrays, such as those in the KiK-net database, represent a unique interaction between observed and predicted ground motions. Recent earthquakes in Japan, including the magnitude 9.0 Tohoku earthquake of 11 March 2011, have substantially increased the number of strong-motion records that can be used to compare alternative site response models at large strains, and can subsequently provide insight into the accuracy and precision of site response models. By taking advantage of data from a large number of events and sites in the KiK-net database, I am able to draw broader, more statistically significant conclusions about site response than are otherwise possible. This dissertation has three primary objectives. First, using linear and equivalent-linear site response analyses for 3720 ground motions at 100 KiK-net sites, I identify critical parameters that most greatly contribute to site response uncertainty, and I quantify the ranges over which these site response models provide accurate predictions. Second, I develop and implement a straightforward methodology for modeling nonlinear site response within a general finite element framework, using the concept of overlay elements. Third, at a subset of six KiK-net sites that are most applicable for one-dimensional site response analyses, I further investigate site response uncertainty by performing a detailed set of linear, equivalent-linear, and nonlinear site response analyses, including the overlay finite element model. The contribution of this dissertation is a greater understanding of the predictive capabilities and limitations of existing site response models, offering a step toward improving the modeling of earthquake site response in engineering practice.
Thesis (Ph.D.)--Tufts University, 2012.
Submitted to the Dept. of Civil Engineering.
Advisor: Laurie Baise.
Committee: Laurie Baise, Eric Thompson, Luis Dorfmann, Richard Vogel, David Garman, and David Boore.
Keywords: Civil engineering, and Geological engineering.read less
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