Prediction Model of Shear Wave Velocity by Using SPT Blow Counts Based on the Conditional Probability Framework
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 143, Issue 4
Abstract
Prediction models of shear wave velocity () based on standard penetration test (SPT) blow counts () are widely used in design practice. Recently, a prediction model that uses multiple predictor variables (e.g., and effective overburden stress) was suggested by several researchers to improve prediction capability. However, the application of these models to design practice is limited because calibrating the regression parameters for a site-specific condition is difficult because of multicollinearity in the model. This study describes the problem of this recently suggested prediction model and proposes a calibration procedure to develop a site-specific model. The framework is based on conditional probability theory and can be applied to any site. Two application examples are presented to develop the site-specific model depending on data availabilities. The first application considers a site where only are available from several borings, and the second application considers a site where both and are available from several locations. The examples show that the conditional probability approach is useful to obtain the site-specific prediction model.
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Acknowledgments
The authors appreciate the support for this study given by the Pacific Engineering Research Center at University of California, Berkeley. The authors also thank the National Center for Earthquake Engineering in Taiwan (NCREE), National Research Institute for Earth Science and Disaster Prevention in Japan (NIED), Chiba Prefecture in Japan, Port and Airport Research Institute in Japan (PARI), and AECOM Technology Corporation (formerly URS Corporation) for providing data. Finally, the authors appreciate two anonymous reviewers for comments that improved the quality of the paper.
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Journal of Geotechnical and Geoenvironmental Engineering
Volume 143 • Issue 4 • April 2017
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©2016 American Society of Civil Engineers.
History
Received: May 19, 2015
Accepted: Aug 16, 2016
Published online: Oct 18, 2016
Discussion open until: Mar 18, 2017
Published in print: Apr 1, 2017
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