An analytical approach to probabilistic modeling of liquefaction based on shear wave velocity
Johari, A; Khodaparast, AR; Javadi, AA
Date: 15 September 2018
Article
Journal
Iranian Journal of Science and Technology Transactions of Civil Engineering
Publisher
Springer
Publisher DOI
Abstract
Evaluation of liquefaction potential of soils is an important step in many geotechnical investigations in
regions susceptible to earthquake. For this purpose, the use of site shear wave velocity (Vs) provides a
promising approach. The safety factors in the deterministic analysis of liquefaction potential are often
difficult to ...
Evaluation of liquefaction potential of soils is an important step in many geotechnical investigations in
regions susceptible to earthquake. For this purpose, the use of site shear wave velocity (Vs) provides a
promising approach. The safety factors in the deterministic analysis of liquefaction potential are often
difficult to interpret because of uncertainties in the soil and earthquake parameters. To deal with the
uncertainties, probabilistic approaches have been employed. In this research, the Jointly Distributed
Random Variables (JDRV) method is used as an analytical method for probabilistic assessment of
liquefaction potential based on measurement of site shear wave velocity. The selected stochastic
parameters are stress-corrected shear-wave velocity and stress reduction factor, which are modeled using
a truncated normal probability density function and the peak horizontal earthquake acceleration ratio and
earthquake magnitude, which are considered to have a truncated exponential probability density function.
Comparison of the results with those of Monte Carlo Simulation (MCS) indicates very good performance of
the proposed method in assessment of reliability. Comparison of the results of the proposed model and a
Standard Penetration Test (SPT)-based model developed using JDRV shows that shear wave velocity (Vs)-
based model provides a more conservative prediction of liquefaction potential than the SPT-base model.
Engineering
Faculty of Environment, Science and Economy
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