Sensitivity of Shallow Foundation Response to Model Input Parameters
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 136, Issue 3
Abstract
From a predictive point of view, it is desirable to characterize the effect of varying model input parameters on the seismic response of soil-foundation systems. In this paper, this issue is studied for shallow foundation systems in dry dense sand with varying vertical factors of safety, embedment depths, demand levels, and moment to shear ratios. Response parameters considered are the moment, shear, sliding, settlement, and rotation demands of the foundation. First-order sensitivity analyses indicate that among the soil input parameters, the friction angle has the most significant effect on capturing the foundation force and displacement demands. Furthermore, the uncertainty in friction angle contributes 80% of the variance of the settlement demand and 40% of the variance of the moment demand. It is also found that the uncertainty in Poisson’s ratio has a marginal effect in predicting the studied foundation response. Although the findings of this study are limited to the parameter space considered herein and care should be taken for broader applicability, it does shed light on which parameters uncertainty should be minimized.
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Acknowledgments
Support for this work was provided by the EERC Program of the National Science Foundation, under Award No. UNSPECIFIEDEEC-9701568, through the Pacific Earthquake Engineering Research Center (PEER). This support is greatly appreciated. Any opinions, findings, and conclusions expressed in this paper are those of the writers, and do not necessarily reflect those of the sponsoring organization. Helpful suggestions from Professors Gajan, Kutter, Stewart, Martin, and Boulanger are greatly appreciated. Use of centrifuge data by researchers at the University of California, Davis, namely, Professors Kutter and Gajan, Key Rosebrook and Jose Ugalde, is much appreciated.
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Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 136 • Issue 3 • March 2010
Pages: 538 - 541
Copyright
© 2010 ASCE.
History
Received: Jan 10, 2009
Accepted: Aug 22, 2009
Published online: Feb 12, 2010
Published in print: Mar 2010
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