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Probabilistic Models for Engineering Assessment of Liquefaction-Induced Lateral Spreading Displacements
University of California, Berkeley, Phd Dissertation, author retains copyright, 2004, PDF
This research effort develops improved engineering tools for prediction of liquefaction-induced lateral spreading displacements. A semi-empirical approach is employed, combining mechanistic understanding and data from laboratory testing with data and lessons from full-scale earthquake field case histories. A formally probabilistic approach is taken to development of the final predictive modelThis research separates the issue of magnitude of liquefaction-induced lateral spread displacement on a lateral spread feature from the spatial distribution of displacements across a lateral spread feature. Magnitude prediction was accomplished by the development of probabilistic predictive models for the estimation of the average and maximum liquefaction-induced lateral spread displacement. Two approaches were developed for prediction of the distribution of lateral displacements across a given spread feature. The first was to define the distribution of displacements at progressively larger distances from the location of maximum displacement, and the second involved assessment of localized strain potential indexes and correlation of these (as well as driving shear stresses and duration of strong shaking) with observed local displacements. Both approaches yielded valuable insight, and the combination of these provide engineering tools for site-specific prediction of liquefaction-induced lateral spreading displacements. The dissertation and two Appendices of supporting data are provided here.
Available online: http://nisee.berkeley.edu/documents/elib/www/documents/2004/faris/