This paper presents a new empirical equation for assessing liquefaction resistance of soils based on shear wave velocity Vs and the results of probabilistic analyses based on this empirical equation. A database consisting of in situ shear wave velocity measurements and field observations of liquefaction/nonliquefaction in historic earthquakes is analyzed. This database is first used to train and test an artificial neural network to predict the occurrence of liquefaction/nonliquefaction based on soil and seismic load parameters. The successfully trained and tested neural network is then used to establish the empirical equation. The concept of clean soil equivalence is introduced and used in the development of the empirical equation. The established empirical equation represents a deterministic method for assessing liquefaction resistance of a soil. Based on this newly developed deterministic method, probabilistic analyses of the cases in the database are conducted using the logistic regression approach and the mapping function approach. The results provide a basis for risk-based evaluation of liquefaction evaluation.
|Number of pages||9|
|Journal||Journal of Geotechnical and Geoenvironmental Engineering|
|State||Published - Aug 2001|