UCLA Geotechnical Engineering
The Geotechnical engineering group at UCLA is among the best earthquake engineering groups in the world. We work on important
topics including liquefaction and cyclic softening, earthquake ground motion characterization, the seismic response of levees, soil-structure interaction,
site response, seismic earth pressures, risk and reliability analysis, applications of geophysical methods to geotechnical engineering problems, and advanced laboratory testing.
We maintain an active group of diverse researchers at all levels, including postdoctoral scholars, PhD, MS, and BS students.
Next Generation Liquefaction
Procedures for engineering assessment of liquefaction hazards are based to a large extent on the interpretation of
field performance data from sites that have or have not experienced ground failure attributable to liquefaction. However, the number of
case histories supporting liquefaction procedures is remarkably small. Given the small number of most relevant case histories, it is no
surprise that existing databases are incomplete, meaning they cannot constrain important components of engineering predictive models.
This unfortunate situation can now be profoundly improved by order-of-magnitude increases in the size and quality of field performance
data sets. The database expansion is to a large extent associated with the devastating earthquakes during 2011 in Japan and New Zealand,
which caused a great deal of damage attributable to liquefaction and its effects. However, numerous other earthquakes have produced data
that has not yet been considered in most of the current liquefaction triggering and effects models, including the 1999 events in Turkey
and Taiwan, 2004 and 2007 events in western Japan, the 2010 event in Chile, and 2010-2011 Canterbury earthquakes in New Zealand.
The Next-Generation Liquefaction (NGL) project was launched to (1) substantially improve the quality, transparency, and accessibility of
case history data related to ground failure; (2) provide a coordinated framework for supporting studies to augment case history data for
conditions important for applications but poorly represented in empirical databases; and (3) provide an open, collaborative process for
model development in which developer teams have access to common resources and share ideas and results during model development, so as to
reduce the potential for mistakes and to mutually benefit from best practices. This approach is motivated in part by the success of the
Next-Generation of Attenuation (NGA) models for ground motion prediction, which has followed this approach and has had substantial global
buy-in and broad application.