A novel approach is introduced to generate simulated ground motion records by considering spectral acceleration correlations at multiple periods. Most of the current reliable Ground Motion Record (GMR) simulation procedures use a seismological model including source, path and site characteristics. However, the response spectrum of simulated GMR is somewhat different when compared with the response spectrum based on recorded GMRs. More specifically, the correlation between the spectral values at multiple periods is a characteristic of a record which is usually different between simulated and recorded GMRs. As this correlation has a significant influence on the structural response, it is needed to investigate the consistency of the simulated ground motions with actual records. This issue has been investigated in this study by incorporating an optimization algorithm within the Boore simulation technique. Eight seismological key parameters were optimized in order to achieve approximately the same correlation coefficients and spectral acceleration between two sets of real and simulated records. The results show that the acceleration response spectra of the synthetic ground motions also have good agreement with the real recorded response spectra by implementation of the proposed optimized values.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Aki K and Richards PG (1980), Quantitative Seismology: Theory and Methods, Vols. I&II, W. H. Freeman, San Francisco, pp. 948.
Azarbakht A and Dolsek M (2011), “Progressive Incremental Dynamic Analysis for First-mode Dominated Structures,” Journal of Structural Engineering, 137: 445–455.
Baker JW and Cornell CA (2005), “A Vector-valued Ground Motion Intensity Measure Consisting of Spectral Acceleration and Epsilon,” Earthquake Engineering and Structural Dynamics, 34: 1193–1217.
Baker JW and Jayaram N (2008), “Correlation of Spectral Acceleration Values from NGA Ground Motion Models,” Earthquake Spectra, 24(1): 299–317.
Beresnev I and Atkinson G (1997), “Modelling Finite Fault Radiation from the ωn Spectrum,” Bulletin of the Seismological Society of America, 87: 67–84.
Beresnev I and Atkinson G (1998), “FINSIM A FORTRAN Program for Simulating Stochastic Acceleration Time Histories from Finite Faults,” Seismological Research Letters, 69: 27–32.
Bommer JJ and Acevedo AB (2004), “The Use of Real Earthquake Accelerograms as Input to Dynamic Analysis,” Journal of Earthquake Engineering, 8: 43–91.
Boore DM (2003), “Simulation of Ground Motion Using the Stochastic Method,” Pure and Applied Geophysics, 160: 635–676.
Goldberg D (1989), Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley: Reading, MA.
Hartzell S (1978), “Earthquake Aftershocks as Green’s Functions,” Geophysics Research Letters, 5: 1–14.
Holland HJ (1975), Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control and Artificial Intelligence, University of Michigan Press, Ann Arbor, MI.
Kroittmaier J (1993), Optimizing Engineering Designs, McGraw-Hill, London, UK.
Kutner M, Nachtsheim C and Neter J (2004), Applied Linear Regression Models, McGraw-Hill/Irwin, New York, pp. 701.
MATLAB, The Language of Technical Computing, Version 220.127.116.119, (R2010a), Available from: http://mathworks.com.
Motazedian D and Atkinson G (2005), “Stochastic Finite-fault Modeling Based on a Dynamic Corner Frequency,” Bulletin of Seismological Society of America, 95: 995–1010.
Mousavi M, Ghafory-Ashtiany M and Azarbakht A (2011), “A New Indicator of Elastic Spectral Shape for the Reliable Selection of Ground Motion Records,” Earthquake Engineering and Structural Dynamics, 40: 1403–1416.
Naeim F, Alimoradi A and Pezeshk S (2004), “Selection and Scaling of Ground Motion Earthquakes for Structural Design Using Genetic Algorithms,” Earthquake Spectra, 20: 413–426.
Naeim F and Lew M (1995), “On the Use of Design Spectrum Compatible Time Histories,” Earthquake Spectra, 11: 111–127.
Pezeshk S, Camp CV and Chen D (2000), “Design of Framed Structures by Genetic Optimization,” Journal of Structural Engineering, 126: 382–388.
Saragoni GR and Hart GC (1974), “Simulation of Artificial Earthquakes,” Earthquake Engineering and Structural Dynamics, 2: 249–267.
Tothong P (2007), “Probabilistic Seismic Demand Analysis Using Advanced Ground Motion Intensity Measures, Attenuation Relationships, and Near-fault Effects,” PhD Dissertation, Stanford University.
Vamvatsikos D and Cornell CA (2002), “Incremental Dynamic Analysis,” Earthquake Engineering and Structural Dynamics, 31: 491–514.
Wells DL and Coppersmith KJ (1994), “New Empirical Relationships among Magnitude, Rupture Length, Rupture Width, Rupture Area and Surface Displacement,” Bulletin of Seismological society of America, 84: 974–1002.
About this article
Cite this article
Azarbakht, A., Sadeghi, M. & Mousavi, M. Ground motion record simulation for structural analysis by consideration of spectral acceleration autocorrelation pattern. Earthq. Eng. Eng. Vib. 13, 195–202 (2014). https://doi.org/10.1007/s11803-014-0223-3
- stochastic method
- simulation ground motion
- random vibration
- site amplification
- EXSIM program