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A faster simulation method for the stochastic response of hysteretic structures subject to earthquakes
Authors:HU Köylüo?lu  SRK Nielsen  A? Çakmak
Institution:College of Arts and Sciences, Koç University, 80860 Istinye, Istanbul, Turkey;Department of Building Technology and Structural Engineering, Aalborg University, DK-9000 Aalborg, Denmark;Department of Civil Engineering and Operations Research, Princeton University, Princeton, NJ 08544, USA
Abstract:A semi-analytical forward-difference Monte Carlo simulation procedure is proposed for the determination of the lower order statistical moments and the joint probability density function of the stochastic response of hysteretic non-linear multi-degree-of-freedom structural systems subject to nonstationary gaussian white noise excitation, as an alternative to conventional direct simulation methods. The method generalizes the so-called Ermak-Allen algorithm developed for simulation applications in molecular dynamics to structural hysteretic systems. The proposed simulation procedure rely on an assumption of local gaussianity during each time step. This assumption is tantamount to various linearizations of the equations of motion. The procedure then applies an analytical convolution of the excitation process, hereby reducing the generation of stochastic processes and numerical integration to the generation of random vectors only. Such a treatment offers higher rates of convergence, faster speed and higher accuracy. The procedure has been compared to the direct Monte Carlo simulation procedure, which uses a fourth-order Runge-Kutta scheme with the white noise process approximated by a broad band Ruiz-Penzien broken line process. The considered system was a multi-dimenensional hysteretic shear frame, where the constitutive equation of the hysteretic shear forces are described by a bilinear hysteretic model. The comparisons show that significant savings in computer time and accuracy can be achieved.
Keywords:Monte Carlo simulations  non-linear random vibration  hysteretic structures  markov processes  MDOF structural systems
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