A REGRESSION MODEL FOR ESTIMATING POWER SPECTRAL DENSITY FUNCTION OF GROUND ACCELERATION
The purpose of this study is to develop a new regression model for power spectral density function (PSDF) of ground acceleration by using the strong motion data of the K-NET and the KiK-NET in Japan. The PSDF is simply expressed as the PA model, proposed by authors before, by using three parameters: the mean square value of the ground acceleration, the predominant frequency, and the shape factor. The regression analyses for the PA-model parameters are carried out based on the maximum likelihood method with respect to the explanatory variables: the distance from the fault to the site, the magnitude, the focal depth, and the averaged shear-wave velocity at the site. The obtained PSDF regression model can express well the averaged tendency, in quality and in quantity, of the observed PSDF. Furthermore, the efficiency and the applicability of the proposed model are demonstrated through the estimation of the earthquake input energy based on the random vibration theory.
Power Spectral Density Function Regression Model Maximum Likelihood Method K-NET KiK-NET
Satoshi Matsuda
Faculty of Environmental and Urban Engineering, Kansai University, Osaka, Japan
国际会议
14th World Conference on Earthquake Engineering(第十四届国际地震工程会议)
北京
英文
2008-10-12（万方平台首次上网日期，不代表论文的发表时间）