Applications of Probabilistic Methods in Geotechnical Engineering. Part 2. Analysis of Documented Case Histories Using a Stochastic Model for Seismically Generated Pore Pressure and Shear Strain Potential,

Abstract

This report presents the basics of a new stochastic model for seismically-generated pore pressure and shear strain potential and illustrates its use for documented case histories. Model parameters are chosen according to available information on the variability of soil properties, and it is applied to sites where liquefaction was observed and where no evidence of liquefaction was observed and where no evidence of liquefaction was observed after major seismic events. Results of the analysis are in substantial agreement with observed field behavior, indicating that this model can be used in a predictive capacity if parameters are chosen correctly. An application of the model to a comprehensive risk analysis of seismically induced initial liquefaction is also briefly described. An example using available seismic information for a hypothetical soil site near San Francisco is presented to illustrate the use of this type of model. Two models are applied to documented case histories to demonstrate their applicability and to illustrate how the probabilistic design parameters are chosen. The probabilistic pore pressure model developed by Chameau (1980) and the probabilistic shear strain model developed by Hadj Hamou (1982) are used herein to analyze the behavior of three sites where liquefaction did and did not occur during earthquakes.

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1983
Accession Number
ADP002383

Entities

People

  • E. Kavazanjian Jr.
  • G. W. Clough
  • J. L. Chameau
  • T. Hadk-hamou

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Agreements
  • Civil Engineering
  • Earthquake Engineering
  • Earthquakes
  • Engineering
  • Geotechnical Engineering
  • Mississippi
  • Pore Pressure
  • Risk
  • Risk Analysis
  • Vulnerability

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Geotechnical Engineering.
  • Systems Analysis and Design