DOI QR코드

DOI QR Code

Correlation of response spectral values in Japanese ground motions

  • Jayaram, Nirmal (Department of Civil and Environmental Engineering, Stanford University) ;
  • Baker, Jack W. (Department of Civil and Environmental Engineering, Stanford University) ;
  • Okano, Hajime (Kajima Corporation) ;
  • Ishida, Hiroshi (Kajima Corporation) ;
  • McCann, Martin W. Jr. (Department of Civil and Environmental Engineering, Stanford University) ;
  • Mihara, Yoshinori (Kajima Corporation)
  • Received : 2010.07.14
  • Accepted : 2011.05.11
  • Published : 2011.12.25

Abstract

Ground motion models predict the mean and standard deviation of the logarithm of spectral acceleration, as a function of predictor variables such as earthquake magnitude, distance and site condition. Such models have been developed for a variety of seismic environments throughout the world. Some calculations, such as the Conditional Mean Spectrum calculation, use this information but additionally require knowledge of correlation coefficients between logarithmic spectral acceleration values at multiple periods. Such correlation predictions have, to date, been developed primarily from data recorded in the Western United States from active shallow crustal earthquakes. This paper describes results from a study of spectral acceleration correlations from Japanese earthquake ground motion data that includes both crustal and subduction zone earthquakes. Comparisons are made between estimated correlations for Japanese response spectral ordinates and correlation estimates developed from Western United States ground motion data. The effect of ground motion model, earthquake source mechanism, seismic zone, site conditions, and source to site distance on estimated correlations is evaluated and discussed. Confidence intervals on these correlation estimates are introduced, to aid in identifying statistically significant differences in correlations among the factors considered. Observed general trends in correlation are similar to previous studies, with the exception of correlation of spectral accelerations between orthogonal components, which is seen to be higher here than previously observed. Some differences in correlations between earthquake source zones and earthquake mechanisms are observed, and so tables of correlations coefficients for each specific case are provided.

Keywords

References

  1. Abrahamson, N.A., Kammerer, A. and Gregor, N. (2003), Summary of scaling relations for spectral damping, peak velocity, and average spectral acceleration: report for the PEGASOS project, Personal communication.
  2. Abrahamson, N.A. and Silva, W. (1997), "Empirical response spectral attenuation relations for shallow crustal earthquakes", Seismol. Res. Lett., 68(1), 94-127. https://doi.org/10.1785/gssrl.68.1.94
  3. Aoi, S., Obara, K., Hori, S., Kasahara, K. and Okada, Y. (2000), "New strong-motion observation network: KiKnet", EOS Trans. Am. Geophys. Union, 81.
  4. Baker, J.W. and Cornell, C.A. (2005), "Vector-valued ground motion intensity measures for probabilistic seismic demand analysis", Report No. 150, John A. Blume Earthquake Engineering Center, Stanford, CA, 321p.
  5. Baker, J.W. and Cornell, C.A. (2006a), "Correlation of response spectral values for multi-component ground motions", B. Seismol. Soc. Am., 96(1), 215-227. https://doi.org/10.1785/0120050060
  6. Baker, J.W. and Cornell, C.A. (2006b), "Spectral shape, epsilon and record selection", Earthq. Eng. Struct. Dyn., 35(9), 1077-1095. https://doi.org/10.1002/eqe.571
  7. Baker, J.W. and Jayaram, N. (2008), "Correlation of spectral acceleration values from NGA ground motion models", Earthq. Spectra, 24(1), 299-317. https://doi.org/10.1193/1.2857544
  8. Bazzurro, P. and Cornell, C.A. (2002), "Vector-valued probabilistic seismic hazard analysis", 7th U.S. National Conference on Earthquake Engineering, Earthquake Engineering Research Institute, Boston, MA, 10p.
  9. Bazzurro, P., Tothong, P. and Park, J. (2009), "Efficient approach to vector-valued probabilistic seismic hazard analysis of multiple correlated ground motion parameters", International Conference on Structural Safety and Reliability (ICOSSAR09), Osaka, Japan, 7p.
  10. Boore, D.M. and Atkinson, G.M. (2008), "Ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods between 0.01 s and 10.0 s", Earthq. Spectra, 24(1), 99-138. https://doi.org/10.1193/1.2830434
  11. Building Seismic Safety Council (1997), NEHRP recommended provisions for seismic regulations for new buildings and other structures, Part 1: Provisions, FEMA 302, Federal Emergency Management Agency.
  12. Gulerce, Z. and Abrahamson, N.A. (2011), "Site-specific design spectra for vertical ground motion", Earthq. Spectra. (in press)
  13. Inoue, T. and Cornell, C.A. (1990), "Seismic hazard analysis of multi-degree-of-freedom structures", Report #RMS-8, Reliability of Marine Structures, Stanford, CA, 70p.
  14. Ishida, H. (1993), "Probabilistic evaluation of earthquake response spectrum and its application to response analysis", Proceedings, 6th International Conference on Structural Safety and Reliability, Innsbruck, Austria, 8.
  15. Kanno, T., Narita, A., Morikawa, N., Fujiwara, H. and Fukushima, Y. (2006), "A new attenuation relation for strong ground motion in Japan based on recorded data", B. Seismol. Soc. Am., 96(3), 879-897. https://doi.org/10.1785/0120050138
  16. Kinoshita, S. (1998), "Kyoshin Net (K-NET), Seismol. Res. Lett., 69, 309-334. https://doi.org/10.1785/gssrl.69.4.309
  17. Kutner, M.H., Nachtsheim, C. and Neter, J. (2004), Applied linear regression models, McGraw-Hill/Irwin, Boston, New York.

Cited by

  1. Dependence of correlations between spectral accelerations at multiple periods on magnitude and distance vol.43, pp.8, 2014, https://doi.org/10.1002/eqe.2393
  2. On computation of conditional mean spectrum in Eastern Canada vol.19, pp.2, 2015, https://doi.org/10.1007/s10950-014-9476-6
  3. New fuzzy method in choosing Ground Motion Prediction Equation (GMPE) in probabilistic seismic hazard analysis vol.10, pp.2, 2016, https://doi.org/10.12989/eas.2016.10.2.389
  4. Site-Corrected Magnitude- and Region-Dependent Correlations of Horizontal Peak Spectral Amplitudes vol.33, pp.4, 2017, https://doi.org/10.1193/091416EQS150M
  5. Occurrence mechanism of recent large earthquake ground motions at nuclear power plant sites in Japan under soil-structure interaction vol.4, pp.5, 2013, https://doi.org/10.12989/eas.2013.4.5.557
  6. Seismic response analysis of layered soils considering effect of surcharge mass using HFTD approach. Part II: Nonlinear HFTD and numerical examples vol.6, pp.6, 2014, https://doi.org/10.12989/gae.2014.6.6.531
  7. Seismic response analysis of layered soils considering effect of surcharge mass using HFTD approach. Part Ι: basic formulation and linear HFTD vol.6, pp.6, 2014, https://doi.org/10.12989/gae.2014.6.6.517
  8. Damping Reduction Factors for Crustal, Inslab, and Interface Earthquakes Characterizing Seismic Hazard in Southwestern British Columbia, Canada vol.32, pp.1, 2016, https://doi.org/10.1193/061414EQS086M
  9. Ground-Motion Prediction Equations based on refined data for dynamic time-history analysis vol.11, pp.5, 2016, https://doi.org/10.12989/eas.2016.11.5.779
  10. Average spectral acceleration: Ground motion duration evaluation vol.14, pp.6, 2011, https://doi.org/10.12989/eas.2018.14.6.577
  11. MCS‐Based PSHA Procedure and Generation of Site‐Specific Design Spectra for the Seismicity Characteristics of China vol.108, pp.a5, 2011, https://doi.org/10.1785/0120170310
  12. Evaluation of the Interperiod Correlation of Ground‐Motion Simulations vol.108, pp.6, 2011, https://doi.org/10.1785/0120180095
  13. A study on sensitivity of seismic site amplification factors to site conditions for bridges vol.51, pp.4, 2018, https://doi.org/10.5459/bnzsee.51.4.197-211
  14. An Empirical Model for the Interfrequency Correlation of Epsilon for Fourier Amplitude Spectra vol.109, pp.3, 2019, https://doi.org/10.1785/0120180238
  15. Impacts of Simulated M9 Cascadia Subduction Zone Motions on Idealized Systems vol.35, pp.3, 2011, https://doi.org/10.1193/052418eqs123m
  16. Interperiod Correlation Model for Mexican Interface Earthquakes vol.35, pp.3, 2011, https://doi.org/10.1193/080918eqs200m
  17. A New State‐of‐the‐Art Platform for Probabilistic and Deterministic Seismic Hazard Assessment vol.90, pp.6, 2011, https://doi.org/10.1785/0220190025
  18. Correlations of spectral accelerations in the Chilean subduction zone vol.36, pp.2, 2011, https://doi.org/10.1177/8755293019891723
  19. Design strategies to achieve target collapse risks for reinforced concrete wall buildings in sedimentary basins vol.36, pp.3, 2011, https://doi.org/10.1177/8755293019899965
  20. Correlation of spectral acceleration values in Iranian ground motions vol.129, pp.1, 2020, https://doi.org/10.1007/s12040-020-01439-4
  21. Empirical Correlations between Generalized Ground-Motion Intensity Measures for Earthquakes in China vol.111, pp.1, 2021, https://doi.org/10.1785/0120200179
  22. Implementing horizontal-to-vertical Fourier spectral ratios and spatial correlation in a ground-motion prediction equation to predict site effects vol.37, pp.2, 2011, https://doi.org/10.1177/8755293020952449
  23. Ground-Motion Intensity Measure Correlations on Interface and Intraslab Subduction Zone Earthquakes Using the NGA-Sub Database vol.111, pp.3, 2011, https://doi.org/10.1785/0120200297
  24. haselREC: an automated open-source ground motion record selection and scaling tool vol.19, pp.14, 2021, https://doi.org/10.1007/s10518-021-01214-w