CONDITIONAL SIMULATION OF GAUSSIAN STOCHASTIC FIELDS FOR EARTHQUAKE GROUND MOTION

Stochastic Model for Earthquake Ground Motion Using Wavelet Packets

For performance-based design, nonlinear dynamic structural analysis using various types of input ground motions is required. Stochastic (simulated) ground motions are sometimes useful as input motions, because their properties can be varied systematically to study the impact of ground-motion properties on structural response, and producing large numbers of ground motions is simple. This paper d...

Earthquake Ground Motion

Simulation of earthquake rupture process and strong ground motion

Computer simulation of the strong ground motion generated from the earthquake•rupture process on a shallow strike-slip fault are carried out by using a 3-D finite difference method. The faulting process is modeled using a dynamic crack model with fixed rupture velocity or with finite-stress-fracture criterion. The near-source ground motion is sensitive to the details of sliprate or slip-acceler...

Analysis and Simulation of Earthquake Strong Ground Motion for Earthquake Engineering Applications (2003-2004)

The objectives of this task are to conduct research on seismic hazards, and to provide relevant input on the expected levels of these hazards to other tasks. Other tasks requiring this input include those dealing with inventory, fragility curves, rehabilitation strategies and demonstration projects. The corresponding input is provided in various formats depending on the intended use: as peak gr...

Neural Gaussian Conditional Random Fields

We propose a Conditional Random Field (CRF) model for structured regression. By constraining the feature functions as quadratic functions of outputs, the model can be conveniently represented in a Gaussian canonical form. We improved the representational power of the resulting Gaussian CRF (GCRF) model by (1) introducing an adaptive feature function that can learn nonlinear relationships betwee...