SYNTHESIS OF RANDOM INPUT MOTION BY FAULT MODEL AND NON-LINEAR RESPONSE ANALYSIS

Non-linear response analysis of building using stochastic RMS Method, part 2

Abstract

 The random phase of artificial input ground motion model for structural design has non-ignorable influence on structural responses. For the case of using the statistical Green’s function method, the maximum acceleration of generated ground motion could fluctuate with the random phase of the elemental earthquake in the range of 20 to 30%. Therefore, the near-average model is often selected as the input ground motion model for structural design in considerably large set of ground motion models with different random phases. To overcome this inconvenience, a new method is presented for generating random input ground motion model expressed as non-stationary power spectral density function. The non-stationary power spectral density function of input ground motion model is synthesized from that of the elemental earthquake and the fault rupture process based on the application of the statistical or empirical Greenʼs function method. Furthermore, the method of estimating the standard deviation and average maximum response of non-linear structure under the random excitation characterized by the non-stationary power spectral density function is presented based on the random vibration theory and the equivalent linearization method. The efficiency of the presented method is investigated through some numerical simulations.

 The non-stationary power spectral density function models of the hypothetical Nankai and Uemachi earthquakes are generated by the presented method; their root mean square acceleration time histories show good agreement with the results of Monte Carlo simulations (MCS). Furthermore, the non-linear responses of an 8-story RC building excited by these two input ground motion models is calculated based on the random vibration theory. The presented method gives good estimation of the expected value of the maximum response with the ductility factor less than about 2 for the case of the Nankai earthquake, whereas the discrepancy with the MCS results increases for large ductility factors concentrated in lower stories observed in the case of the Uemachi earthquake.