Validation of Ground-Motion Simulations through Simple Proxies for the Response of Engineered Systems

We propose a list of simple parameters that act as proxies for the response of more complicated engineered systems and therefore can be studied to validate new methods of ground-motion simulation for engineering applications. The primary list of parameters includes correlation of spectral acceleration across periods, ratio of maximum-to-median spectral acceleration across all horizontal orientations, and the ratio of inelastic-to-elastic displacement, all of which have reliable empirical mod- els against which simulations can be compared. We also describe several secondary parameters, such as directivity pulse period and structural collapse capacity, that do not have robust empirical models but are important for engineering analysis. We then demonstrate the application of these parameters to exemplify simulations computed using a variety of methods, including stochastic finite fault, Graves-Pitarka hybrid broadband, and a composite source model. In general, each simulation method matches empirical models for some parameters and not others, indicating that all rel- evant parameters need to be carefully validated. Online Material: Tables of ground-motion records and simulations selected to have comparable response spectra, and MATLAB code to compute simple proxies for the response of engineering systems.

[1]  A. Veletsos,et al.  Effect of Inelastic Behavior on the Response of Simple Systems to Earthquake Motions , 1975 .

[2]  Pengcheng Liu,et al.  Calculation of Broadband Time Histories of Ground Motion, Part II: Kinematic and Dynamic Modeling Using Theoretical Green’s Functions and Comparison with the 1994 Northridge Earthquake , 2005 .

[3]  E. Miranda.  INELASTIC DISPLACEMENT RATIOS FOR STRUCTURES ON FIRM SITES , 2000 .

[4]  P. Somerville.  Magnitude scaling of the near fault rupture directivity pulse , 2003 .

[5]  Jack W. Baker,et al.  NGA-West2 Models for Ground Motion Directionality , 2014 .

[6]  Wilfred D. Iwan,et al.  Estimating inelastic response spectra from elastic spectra , 1980 .

[7]  H. Krawinkler,et al.  Effects of Near-Fault Ground Motions on Frame Structures , 2001 .

[8]  Yuehua Zeng,et al.  A composite source model for computing realistic synthetic strong ground motions , 1994 .

[9]  N. Abrahamson,et al.  Characterizing Crustal Earthquake Slip Models for the Prediction of Strong Ground Motion , 1999 .

[10]  L. Ibarra.  Global collapse of frame structures under seismic excitations , 2003 .

[11]  G. Atkinson,et al.  Modeling finite-fault radiation from the ωn spectrum , 1997, Bulletin of the Seismological Society of America.

[12]  J. Stewart,et al.  Prediction Equations for Significant Duration of Earthquake Ground Motions considering Site and Near-Source Effects , 2006 .

[13]  J. Baker,et al.  Correlation of Spectral Acceleration Values from NGA Ground Motion Models , 2008 .

[14]  C. Allin Cornell,et al.  Probabilistic seismic demand analysis of nonlinear structures , 1999 .

[15]  Jack W. Baker,et al.  Quantitative Classification of Near-Fault Ground Motions Using Wavelet Analysis , 2007 .

[16]  Babak Alavi-Shushtari,et al.  Effects of Near-Fault Ground Motions on Frame Structures , 2000 .

[17]  Thomas M. Brocher,et al.  Ground-Motion Modeling of the 1906 San Francisco Earthquake, Part I: Validation Using the 1989 Loma Prieta Earthquake , 2008 .

[18]  Gail M. Atkinson,et al.  Stochastic Finite-Fault Modeling Based on a Dynamic Corner Frequency , 2005 .

[19]  J. Bray,et al.  Characterization of forward-directivity ground motions in the near-fault region , 2004 .

[20]  J. Schmedes,et al.  Correlation of earthquake source parameters inferred from dynamic rupture simulations , 2010 .

[21]  Farzin Zareian,et al.  Validation of Ground‐Motion Simulations for Historical Events Using SDoF Systems , 2012 .

[22]  Steven M. Day,et al.  Misfit Criteria for Quantitative Comparison of Seismograms , 2006 .

[23]  Andrejs Jurkevics,et al.  Representing and simulating strong ground motion , 1978 .

[24]  Jonathan P. Stewart,et al.  Calibration of a Semi-Stochastic Procedure for Simulating High-Frequency Ground Motions , 2013 .

[25]  Shawn Larsen,et al.  Calculation of broadband time histories of ground motion: Comparison of methods and validation using strong-ground motion from the 1994 Northridge earthquake , 1999, Bulletin of the Seismological Society of America.

[26]  Jack W. Baker,et al.  An Empirically Calibrated Framework for Including the Effects of Near-Fault Directivity in Probabilistic Seismic Hazard Analysis , 2011 .

[27]  Kim B. Olsen,et al.  Goodness-of-fit Criteria for Broadband Synthetic Seismograms, with Application to the 2008 Mw 5.4 Chino Hills, California, Earthquake , 2010 .

[28]  D. Boore.  Stochastic simulation of high-frequency ground motions based on seismological models of the radiated spectra , 1983 .

[29]  C. Allin Cornell,et al.  An Empirical Ground-Motion Attenuation Relation for Inelastic Spectral Displacement , 2006 .

[30]  Iunio Iervolino,et al.  Spectral shape-based assessment of SDOF nonlinear response to real, adjusted and artificial accelerograms , 2010 .

[31]  John G. Anderson,et al.  QUANTITATIVE MEASURE OF THE GOODNESS-OFFIT OF SYNTHETIC SEISMOGRAMS , 2002 .

[32]  Farzin Zareian,et al.  Basic concepts and performance measures in prediction of collapse of buildings under earthquake ground motions , 2009 .

[33]  J. Bommer,et al.  Relationships between Median Values and between Aleatory Variabilities for Different Definitions of the Horizontal Component of Motion , 2006 .

[34]  A. Pitarka,et al.  Broadband Ground-Motion Simulation Using a Hybrid Approach , 2010 .

[35]  Julian J. Bommer,et al.  The Variability of Ground-Motion Prediction Models and Its Components , 2010 .

[36]  Jonathan P. Stewart,et al.  Comparison of Ground Motions from Hybrid Simulations to NGA Prediction Equations , 2011 .

[37]  Anil K. Chopra,et al.  Dynamics of Structures: Theory and Applications to Earthquake Engineering , 1995 .

[38]  김기범,et al.  Dynamics of Structures : Theory and Applications to Earthquake Engineering, Second Edition , 2010 .

[39]  Kim B. Olsen,et al.  Hybrid Broadband Ground-Motion Simulations : Combining Long-Period Deterministic Synthetics with High-Frequency Multiple StoS Backscattering , 2010 .

[40]  Benjamin Edwards,et al.  Ground motion prediction equations , 2014 .

[41]  Mahmoud M. Hachem,et al.  Ground Motion Prediction Equation (“Attenuation Relationship”) for Inelastic Response Spectra , 2010 .

[42]  G. Ahmadi,et al.  Simulation of earthquake records using time-varying Arma (2,1) model , 2002 .

[43]  N. Jayaram,et al.  A Statistical Analysis of the Response of Tall Buildings to Recorded and Simulated Ground Motions , 2012 .

[44]  Farzin Zareian,et al.  Validation of ground‐motion simulations for historical events using MDoF systems , 2013 .

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

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

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

[48]  D. Boore.  Orientation-independent, nongeometric-mean measures of seismic intensity from two horizontal components of motion , 2010 .

[49]  Kim B. Olsen,et al.  Hybrid Broadband Ground-Motion Simulations: Combining Long-Period Deterministic Synthetics with High-Frequency Multiple S-to-S Backscattering , 2010 .

[50]  Armen Der Kiureghian,et al.  An evolutionary model for earthquake ground motion , 1989 .

[51]  N. Abrahamson,et al.  Modification of Empirical Strong Ground Motion Attenuation Relations to Include the Amplitude and Duration Effects of Rupture Directivity , 1997 .

[52]  N. Abrahamson,et al.  Orientation-Independent Measures of Ground Motion , 2006 .