Skip to main content
Log in

Ground-motion models for average spectral acceleration in a period range: direct and indirect methods

  • Original Research Paper
  • Published:
Bulletin of Earthquake Engineering Aims and scope Submit manuscript

Abstract

Average spectral acceleration, AvgSA, is defined as the geometric mean of spectral acceleration values over a range of periods and it is a ground motion intensity measure used for structural response prediction. One of its advantages stands on the assumption that its distribution is computable from the available GMPEs for spectral acceleration, GMPE-SA, (called here indirect method) without the need for deriving new specific GMPEs for AvgSA, GMPE-AvgSA, (called here direct method). To what extent this assumption is valid, however, has never been verified. As such, we derived an empirical GMPE-AvgSA based on RESORCE ground motion dataset and we compared its predicted values with those from a GMPE-SA via the indirect approach. As expected, the results show that the indirect approach yields median AvgSA estimates that are identical to those of the direct approach. However, the estimates of AvgSA variance of the two methods are identical only if both the GMPE-SA and their empirical correlation coefficients among different SA ordinates are derived from the same record dataset.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8

Similar content being viewed by others

References

  • Abrahamson NA, Silva WJ (1997) Empirical response spectral attenuation relations for shallow crustal earthquakes. Seismol Res Lett 68(1):94–127

    Article  Google Scholar 

  • Abrahamson NA, Youngs RR (1992) A stable algorithm for regression analysis using the random effects model. Bull Seismol Soc Am 82(1):505–510

    Google Scholar 

  • Akkar S, Sandıkkaya MA, Ay BÖ (2014a) Compatible ground-motion prediction equations for damping scaling factors and vertical-to-horizontal spectral amplitude ratios for the broader Europe region. Bull Earthq Eng 12(1):517–547

    Article  Google Scholar 

  • Akkar S, Sandıkkaya MA, Bommer JJ (2014b) Empirical ground-motion models for point- and extended source crustal earthquake scenarios in Europe and the Middle East. Bull Earthq Eng 12:359–387

    Article  Google Scholar 

  • Akkar S, Sandikkaya MA, Senyurt M, Sisi AA, Ay BÖ, Traversa P, Douglas J, Cotton F, Luzi L, Hernandez B, Godey S (2014c) Reference database for seismic ground-motion in Europe (RESORCE). Bull Earthq Eng 12(1):311–339

    Article  Google Scholar 

  • Ambraseys N, Smit P, Douglas J, Margaris B, Sigbjörnsson R, Olafsson S, Suhadolc P, Costa G (2004) Internet site for European strong-motion data. Boll Geofis Teor Appl 45(3):113–129

    Google Scholar 

  • Baker JW (2010) Conditional mean spectrum: tool for ground-motion selection. J Struct Eng 137(3):322–331

    Article  Google Scholar 

  • Baker JW, Bradley BA (2017) Intensity measure correlations observed in the NGA-West2 database, and dependence of correlations on rupture and site parameters. Earthq Spectra 33(1):145–156

    Article  Google Scholar 

  • Baker JW, Cornell CA (2005) A vector-valued ground motion intensity measure consisting of spectral acceleration and epsilon. Earthq Eng Struct Dyn 34(10):1193–1217

    Article  Google Scholar 

  • Baker JW, Cornell CA (2006) Spectral shape, epsilon and record selection. Earthq Eng Struct Dyn 35(9):1077–1095

    Article  Google Scholar 

  • Baker JW, Jayaram N (2008) Correlation of spectral acceleration values from NGA ground motion models. Earthq Spectra 24:299–317

    Article  Google Scholar 

  • Bates D, Mächler M, Bolker B, Walker S (2014) Fitting linear mixed-effects models using lme4. arXiv:1406.5823

  • Bianchini M, Diotallevi P, Baker JW (2009) Prediction of inelastic structural response using an average of spectral accelerations. In: Proceedings, 10th International conference on structural safety and reliability (ICOSSAR09), Osaka

  • Bindi D, Massa M, Luzi L, Ameri G, Pacor F, Puglia R, Augliera P (2014) Pan-European ground-motion prediction equations for the average horizontal component of PGA, PGV, and 5%-damped PSA at spectral periods up to 3.0 s using the RESORCE dataset. Bull Earthq Eng 12(1):391–430

    Article  Google Scholar 

  • Bindi D, Cotton F, Kotha SR, Bosse C, Stromeyer D, Grünthal G (2017) Application-driven ground motion prediction equation for seismic hazard assessments in non-cratonic moderate-seismicity areas. J Seismol 2017:1–18

    Google Scholar 

  • Bojórquez E, Iervolino I (2011) Spectral shape proxies and nonlinear structural response. Soil Dyn Earthq Eng 31(7):996–1008

    Article  Google Scholar 

  • Boore DM, Stewart JP, Seyhan E, Atkinson GM (2014) NGA-West2 equations for predicting PGA, PGV, and 5% damped PSA for shallow crustal earthquakes. Earthq Spectra 30(3):1057–1085

    Article  Google Scholar 

  • Brune JN (1970) Tectonic stress and the spectra of seismic shear waves from earthquakes. J Geophys Res 75(26):4997–5009

    Article  Google Scholar 

  • Campbell KW (1981) Near-source attenuation of peak horizontal acceleration. Bull Seismol Soc Am 71(6):2039–2070

    Google Scholar 

  • Chiou BSJ, Youngs R (2008) An NGA model for the average horizontal component of peak ground acceleration and response spectra. Earthq Spectra 24(1):173–215

    Article  Google Scholar 

  • Chiou BS-J, Youngs RR (2014) Update of the Chiou and Youngs NGA Model for the Average Horizontal Component of Peak Ground Motion and Response Spectra. Earthquake Spectra 30(3):1117–1153

    Article  Google Scholar 

  • Chiou BSJ, Darragh R, Gregor N, Silva W (2008) NGA project strong-motion database. Earthq Spectra 24(1):23–44

    Article  Google Scholar 

  • Cordova PP, Deierlein GG, Mehanny SS, Cornell CA (2000) Development of a two-parameter seismic intensity measure and probabilistic assessment procedure. In: Proceedings, 2nd US–Japan workshop on performance-based earthquake engineering methodology for RC building structures, Sapporo, Hokkaido

  • Cornell CA, Krawinkler H (2000) Progress and challenges in seismic performance assessment. PEER Cent News 3:1–3

    Google Scholar 

  • De Biasio M, Grange S, Dufour F, Allain F, Petre-Lazar I (2014) A simple and efficient intensity measure accounting for non-linear structural behavior. Earthq Spectra 30(4):1403–1426

    Article  Google Scholar 

  • De Biasio M, Grange S, Dufour F, Allain F, Petre-Lazar I (2015) Intensity measures for probabilistic assessment of non-structural components acceleration demand. Earthq Eng Struct Dyn 44:2261–2280

    Article  Google Scholar 

  • Douglas J, Akkar S, Ameri G, Bard PY, Bindi D, Bommer JJ et al (2014) Comparisons among the five ground-motion models developed using RESORCE for the prediction of response spectral accelerations due to earthquakes in Europe and the Middle East. Bull Earthq Eng 12(1):341–358

    Article  Google Scholar 

  • Eads L, Miranda E, Lignos DG (2015) Average spectral acceleration as an intensity measure for collapse risk assessment. Earthq Eng Struct Dyn. doi:10.1002/eqe.2575

    Google Scholar 

  • Eads L, Miranda E, Lignos DG (2016) Spectral shape metrics and structural collapse potential. Earthq Eng Struct Dyn. doi:10.1002/eqe.2739

    Google Scholar 

  • Goda K, Atkinson GM (2009) Probabilistic characterization of spatially correlated response spectra for earthquakes in Japan. Bull Seismol Soc Am 99(5):3003–3020

    Article  Google Scholar 

  • Jayaram N, Baker JW (2008) Statistical tests of the joint distribution of spectral acceleration values. Bull Seismol Soc Am 28:2231–2243

    Article  Google Scholar 

  • Jayaram N, Lin T, Baker JW (2011) A computationally efficient ground-motion selection algorithm for matching a target response spectrum mean and variance. Earthq Spectra 27(3):797–815

    Article  Google Scholar 

  • Kazantzi AK, Vamvatsikos D (2015) Intensity measure selection for vulnerability studies of building classes. Earthq Eng Struct Dyn. doi:10.1002/eqe.2603

    Google Scholar 

  • Kohrangi M, Bazzurro P, Vamvatsikos D (2016a) Vector and scalar IMs in structural response estimation, part I: hazard analysis. Earthq Spectra 32(3):1507–1524

    Article  Google Scholar 

  • Kohrangi M, Bazzurro P, Vamvatsikos D (2016b) Vector and scalar IMs in structural response estimation, part II: building demand assessment. Earthq Spectra 32(3):1525–1543

    Article  Google Scholar 

  • Kohrangi M, Vamvatsikos D, Bazzurro P (2016c) Implications of intensity measure selection for seismic loss assessment of 3-D buildings. Earthq Spectra 32(4):2167–2189

    Article  Google Scholar 

  • Kohrangi M, Bazzurro P, Vamvatsikos D, Spillatura A (2017a) Conditional spectrum-based ground motion selection using average spectral acceleration. Earthq Eng Struct Dyn. doi:10.1002/eqe.2873

    Google Scholar 

  • Kohrangi M, Vamvatsikos D, Bazzurro P (2017b) Site dependence and record selection schemes for building fragility and regional loss assessment. Earthq Eng Struct Dyn. doi:10.1002/eqe.2876

    Google Scholar 

  • Kotha SR, Bindi D, Cotton F (2016) Partially non-ergodic region specific GMPE for Europe and Middle-East. Bull Earthq Eng 14(4):1245–1263

    Article  Google Scholar 

  • Kotha SR, Bindi D, Cotton F (2017) Site-corrected magnitude and region dependent correlations of horizontal peak spectral amplitudes. Earthq Spectra (under review)

  • Koufoudi E, Ktenidou OJ, Cotton F, Dufour Grange S (2015) Empirical ground-motion models adapted to the intensity measure ASA 40. Bull Earthq Eng 13(12):3625–3643

    Article  Google Scholar 

  • Luco N, Cornell CA (2007) Structure-specific scalar intensity measures for near-source and ordinary earthquake ground motions. Earthq Spectra 23(2):357–392

    Article  Google Scholar 

  • Mehanny SSF (2009) A broad-range power-law form scalar-based seismic intensity measure. Eng Struct 31(7):1354–1368

    Article  Google Scholar 

  • R Core Team (2017) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. https://www.R-project.org/

  • Shome N, Cornell CA (1999) Probabilistic seismic demand analysis of nonlinear structures, in John A. Blume Earthquake Engineering Centre. Department of Civil and Environmental Engineering Stanford University

  • Tothong P, Luco N (2007) Probabilistic seismic demand analysis using advanced ground Motion intensity measures. Earthq Eng Struct Dyn 36:1837–1860

    Article  Google Scholar 

  • Vamvatsikos D, Cornell CA (2005) Developing efficient scalar and vector intensity measures for IDA capacity estimation by incorporating elastic spectral shape information. Earthq Eng Struct Dyn 34:1573–1600

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Dr. Dino Bindi for kindly sharing the GMPE R-code used in this study. Useful comments and careful reviews of the paper by Prof. Dimitrios Vamvatsikos, Prof. Fabrice Cotton and two anonymous reviewers are greatly appreciated.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mohsen Kohrangi.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kohrangi, M., Kotha, S.R. & Bazzurro, P. Ground-motion models for average spectral acceleration in a period range: direct and indirect methods. Bull Earthquake Eng 16, 45–65 (2018). https://doi.org/10.1007/s10518-017-0216-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10518-017-0216-5

Keywords

Navigation