Artificial Generation of Spatially Varying of Seismic Ground Motion Using ANNs

Abstract eng:
During an earthquake, the motion of the ground spatially changes, in both amplitude and phase. The spatial variation of seismic ground motions has an important effect on the response of large structures such as bridges and dams. To be able to simulate seismic ground motions which vary in space, a representing spatial variability model is required. Data collected from closely spaced arrays of seismographs such as SMART-1 array in Loting, Taiwan have enabled researchers to produce useful spatial variability models to model spatial excitation. In this paper a simulation technique for the generation of artificial spatially variable seismic ground motions was presented using Arterial Neural Networks (ANNs). A simplified neural network based procedure was used to generate artificial spatial varying accelerograms from the response spectrum of an earthquake.

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