Stochastic Prediction of Seismic Ground Motions Using Macro-Spatial Correlation Model
Estimating a macro-spatial correlation of seismic ground motions is very important for earthquake damage predictions, building portfolio analyses, etc. in which simultaneous damages in different locations have to be taken into consideration. In this study, the residual value between an observed and a ground motion predicted by an empirical mean attenuation equation is focused on. The residual value is now modelled assuming that it constitutes a homogeneous two-dimensional stochastic field in such a way that the joint probability density function (PDF) of seismic ground can be characterized by the spatial correlation model as well as by an empirical mean attenuation equation. Once it can be given in terms of the correlation model with the PDF, stochastic prediction of the ground motion at the locations unobserved can be effectively done with using the data observed at the near-by stations.
KeywordsGround Motion Probability Density Function Peak Ground Acceleration Probabilistic Seismic Hazard Analysis Seismic Ground Motion
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