Orthogonal expansion of ground motion and PDEM-based seismic response analysis of nonlinear structures

This paper introduces an orthogonal expansion method for general stochastic processes. In the method, a normalized orthogonal function of time variable t is first introduced to carry out the decomposition of a stochastic process and then a correlated matrix decomposition technique, which transforms a correlated random vector into a vector of standard uncorrelated random variables, is used to complete a double orthogonal decomposition of the stochastic processes. Considering the relationship between the Hartley transform and Fourier transform of a real-valued function, it is suggested that the first orthogonal expansion in the above process is carried out using the Hartley basis function instead of the trigonometric basis function in practical applications. The seismic ground motion is investigated using the above method. In order to capture the main probabilistic characteristics of the seismic ground motion, it is proposed to directly carry out the orthogonal expansion of the seismic displacements. The case study shows that the proposed method is feasible to represent the seismic ground motion with only a few random variables. In the second part of the paper, the probability density evolution method (PDEM) is employed to study the stochastic response of nonlinear structures subjected to earthquake excitations. In the PDEM, a completely uncoupled one-dimensional partial differential equation, the generalized density evolution equation, plays a central role in governing the stochastic seismic responses of the nonlinear structure. The solution to this equation will yield the instantaneous probability density function of the responses. Computational algorithms to solve the probability density evolution equation are described. An example, which deals with a nonlinear frame structure subjected to stochastic ground motions, is illustrated to validate the above approach.

[1]  M. Shinozuka,et al.  Digital simulation of random processes and its applications , 1972 .

[2]  Roger Ghanem,et al.  Partition of the probability-assigned space in probability density evolution analysis of nonlinear stochastic structures , 2009 .

[3]  Kiyoshi Kanai,et al.  Semi-empirical Formula for the Seismic Characteristics of the Ground , 1957 .

[4]  H. Zhang,et al.  Parameter Analysis of the Differential Model of Hysteresis , 2004 .

[5]  Kok-Kwang Phoon,et al.  Convergence study of the truncated Karhunen–Loeve expansion for simulation of stochastic processes , 2001 .

[6]  R. Ghanem,et al.  Stochastic Finite Element Expansion for Random Media , 1989 .

[7]  K. Phoon,et al.  Comparison between KarhunenLoeve and wavelet expansions for simulation of Gaussian processes , 2004 .

[8]  K. Phoon,et al.  Implementation of Karhunen-Loeve expansion for simulation using a wavelet-Galerkin scheme , 2002 .

[9]  Masanobu Shinozuka,et al.  Simulation of Multivariate and Multidimensional Random Processes , 1971 .

[10]  Mircea Grigoriu,et al.  Evaluation of Karhunen–Loève, Spectral, and Sampling Representations for Stochastic Processes , 2006 .

[11]  Kok-Kwang Phoon,et al.  Simulation of second-order processes using Karhunen–Loeve expansion , 2002 .

[12]  R. Clough,et al.  Dynamics Of Structures , 1975 .

[13]  Y. Wen Method for Random Vibration of Hysteretic Systems , 1976 .

[14]  George W. Housner,et al.  Characteristics of strong-motion earthquakes , 1947 .

[15]  Mariano J. Valderrama,et al.  On the numerical expansion of a second order stochastic process , 1992 .

[16]  A. Kiureghian,et al.  Response spectrum method for multi‐support seismic excitations , 1992 .

[17]  Howard H. M. Hwang,et al.  Probabilistic seismic analysis of a steel frame structure , 1993 .

[18]  Jianbing Chen,et al.  Dynamic response and reliability analysis of structures with uncertain parameters , 2005 .

[19]  Jianbing Chen,et al.  The probability density evolution method for dynamic response analysis of non‐linear stochastic structures , 2006 .

[20]  Jianbing Chen,et al.  Stochastic Dynamics of Structures , 2009 .

[21]  H. Tajimi,et al.  Statistical Method of Determining the Maximum Response of Building Structure During an Earthquake , 1960 .

[22]  Ronald N. Bracewell The Hartley transform , 1986 .

[23]  Masanobu Shinozuka,et al.  Simulation of Multi-Dimensional Gaussian Stochastic Fields by Spectral Representation , 1996 .

[24]  M. Shinozuka,et al.  Simulation of Stochastic Processes by Spectral Representation , 1991 .

[26]  K. Phoon,et al.  Comparison between Karhunen-Loève expansion and translation-based simulation of non-Gaussian processes , 2007 .

[27]  Jianbing Chen,et al.  Probability density evolution method for dynamic response analysis of structures with uncertain parameters , 2004 .

[28]  George Deodatis,et al.  Non-stationary stochastic vector processes: seismic ground motion applications , 1996 .

[29]  H. Keng,et al.  Applications of number theory to numerical analysis , 1981 .

[30]  Kok-Kwang Phoon,et al.  Simulation of non-Gaussian processes using fractile correlation , 2004 .

[31]  Jianbing Chen,et al.  The Number Theoretical Method in Response Analysis of Nonlinear Stochastic Structures , 2007 .

[32]  Bruce R. Ellingwood,et al.  Orthogonal Series Expansions of Random Fields in Reliability Analysis , 1994 .

[33]  G. Deodatis Simulation of Ergodic Multivariate Stochastic Processes , 1996 .

[34]  Jianbing Chen,et al.  The principle of preservation of probability and the generalized density evolution equation , 2008 .

[35]  Jianbing Chen,et al.  Dynamic response and reliability analysis of non-linear stochastic structures , 2005 .