Simulation of orthogonal horizontal ground motion components for specified earthquake and site characteristics

SUMMARY A method for generating an ensemble of orthogonal horizontal ground motion components with correlated parameters for specified earthquake and site characteristics is presented. The method employs a parameterized stochastic model that is based on a time-modulated filtered white-noise process with the filter having time-varying characteristics. Whereas the input white-noise excitation describes the stochastic nature of the ground motion, the forms of the modulating function and the filter and their parameters characterize the evolutionary intensity and nonstationary frequency content of the ground motion. The stochastic model is fitted to a database of recorded horizontal ground motion component pairs that are rotated into their principal axes, a set of orthogonal axes along which the components are statistically uncorrelated. Model parameters are identified for each ground motion component in the database. Using these data, predictive equations are developed for the model parameters in terms of earthquake and site characteristics and correlation coefficients between parameters of the two components are estimated. Given a design scenario specified in terms of earthquake and site characteristics, the results of this study allow one to generate realizations of correlated model parameters and use them along with simulated white-noise processes to generate synthetic pairs of horizontal ground motion components along the principal axes. The proposed simulation method does not require any seed recorded ground motion and is ideal for use in performance-based earthquake engineering. Copyright © 2011 John Wiley & Sons, Ltd.

[1]  J. Penzien,et al.  Analysis of three‐dimensional strong ground motions along principal axes, San Fernando earthquake , 1979 .

[2]  Vitelmo V. Bertero,et al.  Earthquake Engineering: From Engineering Seismology To Performance-Based Engineering , 2020 .

[3]  Sanaz Rezaeian,et al.  Stochastic Modeling and Simulation of Ground Motions for Performance-Based Earthquake Engineering , 2010 .

[4]  David M. Boore,et al.  Simulation of Ground Motion Using the Stochastic Method , 2003 .

[5]  Chin-Hsun Yeh,et al.  Modeling of nonstationary earthquake ground motion and biaxial and torsional response of inelastic structures , 1989 .

[6]  Armen Der Kiureghian,et al.  TAIL EQUIVALENT LINEARIZATION METHOD FOR NONLINEAR RANDOM VIBRATION , 2007 .

[7]  Julio J. Hernández,et al.  Critical response of structures to multicomponent earthquake excitation , 2000 .

[8]  I. M. Idriss,et al.  Comparisons of the NGA Ground-Motion Relations , 2008 .

[9]  J. García-Pérez,et al.  Evolutionary properties of stochastic models of earthquake accelerograms: Their dependence on magnitude and distance , 2001 .

[10]  Masanobu Shinozuka,et al.  Stochastic process models for earthquake ground motion , 1988 .

[11]  C. Menun,et al.  A Replacement for the 30%, 40%, and SRSS Rules for Multicomponent Seismic Analysis , 1998 .

[12]  Joel P. Conte,et al.  Fully nonstationary analytical earthquake ground-motion model , 1997 .

[13]  A. Arias A measure of earthquake intensity , 1970 .

[14]  Cécile Cornou,et al.  Calibrating Median and Uncertainty Estimates for a Practical Use of Empirical Green’s Functions Technique , 2008 .

[15]  K. Campbell,et al.  NGA Ground Motion Model for the Geometric Mean Horizontal Component of PGA, PGV, PGD and 5% Damped Linear Elastic Response Spectra for Periods Ranging from 0.01 to 10 s , 2008 .

[16]  A. Kiureghian,et al.  Modal combination rules for multicomponent earthquake excitation , 1985 .

[17]  A. Kiureghian,et al.  Multivariate distribution models with prescribed marginals and covariances , 1986 .

[18]  Ernesto Heredia-Zavoni,et al.  Response to orthogonal components of ground motion and assessment of percentage combination rules , 2004 .

[19]  Armen Der Kiureghian,et al.  A stochastic ground motion model with separable temporal and spectral nonstationarities , 2008 .

[20]  Nicolas Luco,et al.  Does amplitude scaling of ground motion records result in biased nonlinear structural drift responses? , 2007 .

[21]  Jack W. Baker,et al.  Assessment of Ground Motion Selection and Modification (GMSM) methods for non -linear dynamic analyses of structures , 2008 .

[22]  F. Kozin,et al.  Autoregressive moving average models of earthquake records , 1988 .

[23]  Joseph Penzien,et al.  CHARACTERISTICS OF 3-DIMENSIONAL EARTHQUAKE GROUND MOTIONS , 1974 .

[24]  Arthur Frankel,et al.  A Constant Stress-Drop Model for Producing Broadband Synthetic Seismograms: Comparison with the Next Generation Attenuation Relations , 2009 .

[25]  Ludovic Margerin,et al.  Nonstationary Stochastic Simulation of Strong Ground Motion Time Histories Including Natural Variability: Application to the K-Net Japanese Database , 2006 .

[26]  Farzad Naeim,et al.  On the Use of Design Spectrum Compatible Time Histories , 1995 .

[27]  Francesca Pacor,et al.  Uncertainties in strong ground-motion prediction with finite-fault synthetic seismograms: an application to the 1984 M 5.7 Gubbio, central Italy, earthquake. , 2009 .

[28]  S. C. Liu,et al.  Synthesis of stochastic representations of ground motions , 1970, Bell Syst. Tech. J..

[29]  Pengcheng Liu,et al.  Prediction of Broadband Ground-Motion Time Histories: Hybrid Low/High- Frequency Method with Correlated Random Source Parameters , 2006 .

[30]  Armen Der Kiureghian,et al.  Simulation of synthetic ground motions for specified earthquake and site characteristics , 2010 .