Seismic Performance Uncertainty Estimation via IDA with Progressive Accelerogram-Wise Latin Hypercube Sampling

AbstractAn algorithm is proposed for the rapid estimation of the influence of model parameter uncertainties on the seismic performance of structures using incremental dynamic analysis (IDA) and Monte Carlo simulation with Latin hypercube sampling. It builds upon existing methods that quantify the uncertainty for structural models with nondeterministic parameters by performing IDA with multiple ground motion records on each model realization out of a predetermined sample. However, their practical application is restricted due to (1) the inability to determine a priori the required number of samples and (2) the disproportionate increase of the number of analyses in realistic multiparameter models. To address these issues, two fundamental changes are incorporated. First, Latin hypercube sampling is applied progressively by starting with a small sample that is doubled successively until the desired accuracy is achieved. Second, parameter sampling is performed on a record-by-record basis rather than maintainin...

[1]  M. Dolšek Simplified method for seismic risk assessment of buildings with consideration of aleatory and epistemic uncertainty , 2011 .

[2]  Matjaž Dolšek,et al.  Prediction of the median IDA curve by employing a limited number of ground motion records , 2007 .

[3]  Sonia E. Ruiz,et al.  Seismic Failure Rates of Multistory Frames , 1989 .

[4]  Luis Ibarra,et al.  Variance of collapse capacity of SDOF systems under earthquake excitations , 2011 .

[5]  C. Allin Cornell,et al.  Probabilistic Basis for 2000 SAC Federal Emergency Management Agency Steel Moment Frame Guidelines , 2002 .

[6]  Antonio Bruno Rigato INFLUENCE OF ANGLE OF INCIDENCE ON THE SEISMIC DEMANDS FOR INELASTIC STRUCTURES SUBJECTED TO BI-DIRECTIONAL GROUND MOTIONS , 2007 .

[7]  Douglas A. Foutch,et al.  Modeling of steel moment frames for seismic loads , 2002 .

[8]  Robert Tibshirani,et al.  An Introduction to the Bootstrap , 1994 .

[9]  Dimitrios Vamvatsikos,et al.  Performing incremental dynamic analysis in parallel , 2011 .

[10]  Matjaz Dolsek,et al.  Incremental dynamic analysis with consideration of modeling uncertainties , 2009 .

[11]  Jack W. Baker,et al.  Incorporating modeling uncertainties in the assessment of seismic collapse risk of buildings , 2009 .

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

[13]  Peter Fajfar,et al.  Simplified non‐linear seismic analysis of infilled reinforced concrete frames , 2005 .

[14]  Fatemeh Jalayer,et al.  The probabilistic basis for the 2000 SAC/FEMA steel moment frame guidelines , 2002 .

[15]  Dimitrios Vamvatsikos,et al.  Incremental dynamic analysis , 2002 .

[16]  W. J. Hall,et al.  Recommended Seismic Design Criteria for New Steel Moment-Frame Buildings , 2001 .

[17]  Reginald DesRoches,et al.  Analytical Seismic Fragility Curves for Typical Bridges in the Central and Southeastern United States , 2007 .

[18]  Charles Tong,et al.  Refinement strategies for stratified sampling methods , 2006, Reliab. Eng. Syst. Saf..

[19]  Fatemeh Jalayer,et al.  Alternative non‐linear demand estimation methods for probability‐based seismic assessments , 2009 .

[20]  M. Vořechovský,et al.  Extension of sample size in Latin Hypercube Sampling with correlated variables , 2010 .

[21]  A. Kiureghian,et al.  Aleatory or epistemic? Does it matter? , 2009 .

[22]  Dimitrios Vamvatsikos,et al.  Direct estimation of the seismic demand and capacity of oscillators with multi‐linear static pushovers through IDA , 2006 .

[23]  D. Novák,et al.  CORRELATION CONTROL IN SMALL-SAMPLE MONTE CARLO TYPE SIMULATIONS I: A SIMULATED ANNEALING APPROACH , 2009 .

[24]  Nicolas Luco,et al.  Structure-Specific Scalar Intensity Measures for Near-Source and Ordinary Earthquake Ground Motions , 2007 .

[25]  Dimitrios Vamvatsikos,et al.  Fast performance uncertainty estimation via pushover and approximate IDA , 2009 .

[26]  Nikos D. Lagaros,et al.  Multicomponent incremental dynamic analysis considering variable incident angle , 2010 .

[27]  Richard J. Beckman,et al.  A Comparison of Three Methods for Selecting Values of Input Variables in the Analysis of Output From a Computer Code , 2000, Technometrics.

[28]  Dimitrios Vamvatsikos,et al.  Incremental dynamic analysis for estimating seismic performance sensitivity and uncertainty , 2010 .

[29]  Dimos C. Charmpis,et al.  A heuristic approach for the generation of multivariate random samples with specified marginal distributions and correlation matrix , 2004, Comput. Stat..

[30]  Helmut Krawinkler,et al.  Deterioration Modeling of Steel Components in Support of Collapse Prediction of Steel Moment Frames under Earthquake Loading , 2011 .

[31]  Jon C. Helton,et al.  A method for extending the size of a Latin hypercube sample. , 2005 .

[32]  Marios K. Chryssanthopoulos,et al.  Fragility and Hazard Analysis of a Welded Steel Moment Resisting Frame , 2008 .

[33]  Luis Ibarra,et al.  Hysteretic models that incorporate strength and stiffness deterioration , 2005 .

[34]  R. Iman,et al.  A distribution-free approach to inducing rank correlation among input variables , 1982 .

[35]  Jon C. Helton,et al.  Extension of Latin hypercube samples with correlated variables , 2008, Reliab. Eng. Syst. Saf..

[36]  Fragiadakis Michalis,et al.  Evaluation of the influence of vertical irregularities on the seismic performance of a nine‐storey steel frame , 2006 .

[37]  Matjaž Dolšek,et al.  Progressive Incremental Dynamic Analysis for First-Mode Dominated Structures , 2011 .

[38]  C. V. Anderson,et al.  The Federal Emergency Management Agency (FEMA) , 2002 .