Prediction of the severity of ground failure in Quaternary deposits is a critical component of hazard studies. Model development in our project is focused on design and application of methods for quantitative assessment of ground deformation potential.
Probabilistic Liquefaction Triggering Assessment (Collaborative research with U.C. Berkeley; PEER; Kobe University; and the China Seismological Bureau):
At first step, we are gathering global databases for field measurements of liquefaction resistance by cataloging existing data and collecting new data for penetration-based, and shear wave velocity-based, liquefaction evaluation measurements. To acquire new Vs field profiles, we use a variety of active and passive surface wave methods and analysis techniques at liquefaction evaluation sites already documented by drill logs.
To correlate these databases with likelihood of initiation of seismic-soil liquefaction, we utilize high-order probabilistic tools (Bayesian updating) developed for structural engineering reliability. A multi-parameter limit-state function for liquefaction triggering is modeled and evaluated based on the means, distributions and uncertainties of each model-parameter. Each case history is then sub-divided into 'quality'-ranking categories based on the conjugate-uncertainties of the estimated earthquake induced stress and the measured field-based liquefaction resistance of the ground. A low-pass cut-off in the coefficient of variation is used filter-out poorly constrained sites. Finally for the probabilistic analysis, the Bayesian updating procedure is used to iteratively compute coefficients for the limit-state function that minimize model error. The intended outcome of this effort is a new evaluation of liquefaction-triggering boundaries in light of global data sets and modern limit-state probabilistic tools.
Probabilistic Assessment of Dynamic Displacements: This project is focused on developing probabilistic models for multidirectional seismic shear displacements in soil for liquefiable and non-liquefiable deposits. Bayesian methods, described above, and Newmark-type models for computing seismic slope displacements are used to estimate the amplitude of ground failures during earthquakes.