Evaluation of Ground Motion Selection Techniques for Seismic Rigid Sliding Block Analyses
Publication: Journal of Geotechnical and Geoenvironmental Engineering
Volume 143, Issue 4
Abstract
Seismic sliding block displacements provide a useful index for the seismic performance of a slope and are computed for a suite of acceleration-time histories selected to fit a target ground motion. This paper explores the effect of different ground motion selection techniques on computed rigid sliding block displacements. In particular, capturing the characteristics of ground shaking through the consideration of the additional ground motion parameters that influence sliding displacement [i.e., peak ground velocity (PGV) and Arias intensity (Ia)] is investigated. Rigid sliding block displacements are computed for ground motion suites scaled to a target peak ground acceleration (PGA) and selected using different approaches. Two suites are selected to fit target acceleration response spectra [i.e., uniform hazard spectra (UHS) and conditional mean spectra (CMS)], and three suites are selected to fit conditional probability distributions for PGV and Ia through the generalized conditional intensity measure (GCIM) approach. The PGV and Ia distributions of the UHS suite exceed the target conditional distributions of PGV and Ia. As such, the displacements computed using the UHS suite far exceed the displacements computed for any other suite of motions considered in this study. The PGV and Ia distributions, and the displacements, for the CMS suite align well with those for the suite selected to fit the GCIM target distributions for both PGV and Ia. It is recommended that motions for sliding block analysis be selected to fit the GCIM PGV and Ia distributions conditional on PGA, although motions selected to fit the CMS can generate similar displacement results.
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Acknowledgments
The authors thank Brendon Bradley for sharing his GCIM ground motion selection code, and for extending the capability of the code to consider values of Arias intensity. The authors also thank the two anonymous reviewers of this paper and Prof. Jack Baker of Stanford University, who provided valuable input that improved the manuscript.
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Published In
Journal of Geotechnical and Geoenvironmental Engineering
Volume 143 • Issue 4 • April 2017
Copyright
©2016 American Society of Civil Engineers.
History
Received: Jun 26, 2015
Accepted: Aug 2, 2016
Published online: Nov 23, 2016
Published in print: Apr 1, 2017
Discussion open until: Apr 23, 2017
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