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Pacific Coastal & Marine Science Center

Global Geoengineering Research

Alaska Australia California China Ecuador Grand Canyon Greece Hawaii Italy Japan New Orleans Taiwan Washington State

Photograph of earthquake-damaged buildings in Niigata City, Kawagishi-cho, 1964.

Modeling

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.

  1. Modeling Shear Wave Velocity Structure Using Spectral Analysis of Surface Waves (SASW) techniques (Collaborative with Woods Hole CMG): The SASW technique is ideal for the assessment of ground failure in the coastal and offshore environment principally because of the portability of the apparatus and the non-invasive nature of the technique. For onshore deployments we use a spectrum analyzer and commercially available vertical 1-Hz sensors. For offshore investigation, we use custom designed ocean bottom seismometers (OBS) built into a ship deployable seafloor SASW system. The OBS units are arrayed in a linear multi-station configuration and mounted onto a linear support frame. The surface wave source for onshore and offshore work is an electromechanical shaker. For offshore deployment, the shaker is housed in an air filled vessel and deployed at the end of the support frame. We routinely use the SASW method to develop profiles of shear wave velocity in the upper 30+ meters of the earth. These profiles can be used as part of a liquefaction hazard assessment and as the basis for predicting response of sites to incoming earthquake ground motions.
     
  2. Probabilistic Liquefaction Triggering Assessment (Collaborative research with U.C. Berkeley; PEER; Kobe University; and the China Seismological Bureau):
     
    • The probabilistic models for liquefaction assessment are being advanced along two tracks. First, global data sets are being assembled to identify the ground conditions and earthquake stresses at the majority of the world's documented ground failure sites. To do this we have cataloged existing data sets, and have revisited and tested over 300 sites in China, Japan, Taiwan and the USA. The second track involves modeling these data through a Bayesian updating and structural reliability engine used to assess the probability of failure in a component or system. Here, the system is a geotechnical model of soil resistance to liquefaction occurrence, and the loads are associated with earthquake motion.
       
    • 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.
       
  3. 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.

 

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