1887
Volume 9 Number 6
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

Currently, the use of ambient noise arrays has become fairly routine for site characterization applications. Conventionally, the first step in the analysis of ambient noise arrays is the computation of the dispersion curve, defined as the Rayleigh wave phase velocity dependence on frequency. The second more complex step is the inversion of the dispersion curve to obtain a shear‐wave velocity profile. In many engineering applications, where only the time‐averaged shear‐wave velocity, termed Vs30, is needed, a relationship between the Rayleigh phase wave velocity at a given wavelength, VR(λ), and Vs30 is commonly developed for the specific area of study. We compare the results from two recently proposed inversion strategies, the first one is based on the misfit criteria, the second on the Akaike criteria, which we apply to experimental data acquired from the Euroseistest site in Greece. We also show that the two inversion strategies have their limits: for the first strategy, using misfit criteria and constraints, the restriction of describing the dispersion curve within the frequency band defined from the fundamental frequency to ten times this frequency is sometimes difficult to fulfil. On the other hand, the second strategy, using the Akaike criteria, is time‐consuming and requires large data storage. Finally, we conclude that the VR(λ=37m)‐Vs30 relationship is promising but should be confirmed with more data analysis.

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2011-11-01
2024-04-23
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References

  1. AkiK.1957. Space and time spectra of stationary stochastic waves, with special reference to microtremors. Bulletin Earthquake Research Institute35, 415–456.
    [Google Scholar]
  2. AlbarelloD. and GarganiG.2010. Providing NEHRP Soil Classification from the Direct Interpretation of Effective Rayleigh‐Wave Dispersion Curves. Bulletin of the Seismological Society of America100, No. 6, pp. 3284–3294, December 2010. doi: 10.1785/0120100052
    [Google Scholar]
  3. ApostolidisP., Roumelioti, Z., RaptakisD., PitilakisK.2001. Determination of the shear wave velocities with the use of micro‐tremor data in Euro‐Seistest. Proceedings of the 9th International Congress of the Geological Society of Greece, Athens, 8 pp, (in Greek).
    [Google Scholar]
  4. BardP.‐Y. and SESAME participants. 2004.The SESAME project: An overview and main results. Proceedings of the 13th World Conference in Earthquake Engineering, Vancouver, August 2004, Paper # 2207.
    [Google Scholar]
  5. BardP.‐Y.2007. From noise measurements to site effects: Main perspectives after the SESAME project and ESG2006 blind test. Invited keynote lecture, ISSSR 2007, Bucharest, April 27–28, 2007.
    [Google Scholar]
  6. Bettig, B., BardP.‐Y., ScherbaumF., RieplJ., CottonF., CornouC. and HatzfeldD.2001. Analysis of dense array noise measurements using the modified spatial auto‐correlation method (SPAC). Application to the Grenoble area. Bolletino di Geofisica Teorica ed Applicata, 42, 281–304.
    [Google Scholar]
  7. Boore, D.2006. Determining subsurface shear‐wave velocities: A review. Presented at the Third International Symposium on the effects of surface geology on seismic motion, Grenoble, France, paper number 103.
    [Google Scholar]
  8. BurnhamK. P. and AndersonD.R.2007. Kullback–Leibler information as a basis for strong inference in ecological studies. Wildlife Research, 2001, 28, 111–119.
    [Google Scholar]
  9. CadetH.2007. Utilisation combinée des méthodes basées sur le bruit de fond dans le cadre du microzonage sismique. PhD thesis of the University of Joseph Fourier, Grenoble, October 2007, 300 pages.
    [Google Scholar]
  10. CaponJ.1969. High‐resolution frequency‐wave number spectrum analysis. Proceedings of the IEEE 57, 1969, 1408–1418.
    [Google Scholar]
  11. ChatelainJ.‐L., GuillierB., CaraF., DuvalA.‐M., AtakanK., Bard P.‐Y., AzzaraR., Bonnefoy‐ClaudetS., BorgesA., Bottger SorensenM., CultreraG., Di GiulioG., DunandF., FähD., GuéguenP., RippergerJ., Teves CostaP., VassiliadesJ.‐F., VidalS. and WassnerJ.2008. Evaluation of the influence of experimental conditions on H/V results from ambient noise recordings. Bulletin of Earthquake Engineering6, Number 1, February 2008. DOI: 10.1007/s10518‐007‐9040‐7
    [Google Scholar]
  12. Chávez‐GarcíaF.J., RaptakisD.2008. Inversion of soil structure and analysis of the wavefield from a vertical array. 14th World Conference on Earthquake Engineering, October 12–17, 2008, Beijing, China.
    [Google Scholar]
  13. Chávez‐GarcíaF.J., RaptakisD., MakraK., PitilakisK.2002. Importance of the reference station in modeling site effects up to larger frequencies. The case of Euroseistest. 12th European conference on earthquake engineering, paper reference 589, London.
    [Google Scholar]
  14. CornouC., OhrnbergerM., BooreD., KudoK., and BardP‐Y.2006. Derivation of structural models from ambient vibration array recordings: Results from an international blind test. Third International Symposium on the effects of surface geology on seismic motion, Grenoble, France, pp 92.
    [Google Scholar]
  15. CornouC., RenalierF., Di GiulioG., OhrnbergerM., SavvaidisA., WatheletM., BardP.‐Y.2010. Derivation of Vs30 from dispersion curve: Skipping the inversion step?Proceedings of the ESC2010, Montpellier, session SH4/P31/ID38.
    [Google Scholar]
  16. EN 1998‐1. Eurocode 8
    EN 1998‐1. Eurocode 8 . 1998. Design of structures for earthquake resistance‐ Part 1: General rules, seismic actions and rules for buildings. EN 1998, European committee for standardization.
    [Google Scholar]
  17. EURO‐SEISMOD
    EURO‐SEISMOD . 1998. Development and Experimental Validation of Advanced Modeling Techniques in Engineering Seismology and Earthquake Engineering ‐ EURO‐SEISMOD. Final Scientific Report, Thessaloniki, 1998.
    [Google Scholar]
  18. FotiS., CominaC., BoieroD. and SoccoL.V.2009. Non‐uniqueness in surface‐wave inversion and consequences on seismic site response analyses. Soil Dynamics and Earthquake Engineering29, 982–993.
    [Google Scholar]
  19. GuillierB., AtakanK., ChatelainJ.‐L., HavskovJ., OhrnbergerM., CaraF., DuvalA.‐M., ZacharopoulosS., Teves‐CostaP., AcceraC., AlguacilG., AzzaraR., BardP.‐Y., BlarelF., BorgesA., GrandisonM., RaoS., TheodulidisN., TvedtE., UtheimT., VidalS. and VollmerD.2008. Influence of instruments on the H/V spectral ratios of ambient vibrations. Bulletin of Earthquake Engineering, 2008‐1.
    [Google Scholar]
  20. HaghshenasE., BardP.‐Y., TheodulidisN. and SESAME WP04 Team 2008. Empirical evaluation of microtremor H/V spectral ratio. Bulletin of Earthquake Engineering, Volume 6, Number 1, February 2008. DOI: 10.1007/s10518‐007‐9058‐x
    [Google Scholar]
  21. JongmansD., PitilakisK., DemanetD., RaptakisD., RieplJ., HorrentC., TsokasG., LontzetidisK. and BardP.‐Y.1998. EURO‐SEISTEST: Determination of the Geological Structure of the Volvi Basin and Validation of the Basin Response. Bulletin of the Seismological Society of America88, No. 2, pp. 473–487, April 1998.
    [Google Scholar]
  22. KonnoK. and OhmachiT.1998. Ground‐motion characteristics estimated from spectral ratio between horizontal and vertical components of microtremor. Bulletin of the Seismological Society of America88, pp. 228–241.
    [Google Scholar]
  23. LacossR.T., KellyE.J. and ToksözM.N.1969. Estimation of seismic noise structure using array. Geophysical Journal International163, 169–182.
    [Google Scholar]
  24. ManakouM.2007. Contribution to the determination of a 3‐dimensional earth model for the investigation of seismic response: An application in the sedimentary Mygdonia Basin. PhD Thesis, School of Engineering of the Aristotle University of Thessaloniki, 239 pp, (in Greek with a summary in English).
    [Google Scholar]
  25. MossR.E.2008. Quantifying measurement uncertainty of thirty‐meter shear‐wave velocity. Bulletin of the Seismological Society of America98, No. 3, pp. 1399–1411, June 2008, doi: 10.1785/0120070101.
    [Google Scholar]
  26. NakamuraY.1989. A method for dynamic characteristics estimation of subsurface using microtremor on the ground surface. Quarterly Report Railway Tech. Res. Inst., 30‐1, pp 25–30.
    [Google Scholar]
  27. NEHRP. Building Seismic Safety Council
    NEHRP. Building Seismic Safety Council . 2001. National Earthquake Hazards, Reduction Program (NEHRP) Recommended Provisions for Seismic Regulations for New Buildings and Other Structures, Part 1 – Provisions and Part 2 – Commentary, Reports No. FEMA‐368 and FEMA‐369, prepared by the Building Seismic Safety Council for the Federal Emergency Management Agency, Washington, D.C.
    [Google Scholar]
  28. NogoshiM. and IgarashiT.1971. On the amplitude characteristics of microtremor (part 2). Journal of the Seismological Society of Japan,24, 26–40. (In Japanese with an English abstract).
    [Google Scholar]
  29. RaptakisD., TheodulidisN. and PitilakisK.1998. Data analysis of the Euroseistest strong motion array in Volvi (Greece): Standard and horizontal‐to‐vertical spectral ratio techniques. Earthquake Spectra14, 203–224.
    [Google Scholar]
  30. RaptakisD.G., Chavez‐GarciaF., MakraK.A. and PitilakisK.D.2000. Site Effects at Euroseistest‐I. 2D Determination of the Valley Structure and Confrontation of the Observations with 1D Analysis. Soil Dynamics and Earthquake Engineering,19(1), pp. 1–22.
    [Google Scholar]
  31. RenalierF., JongmansD., SavvaidisA., WatheletM., EndrunB. and CornouC.2010. Influence of parameterisation on inversion of surface wave dispersion curves and definition of an inversion strategy for sites with a strong Vs contrast. Geophysics75, 197–209.
    [Google Scholar]
  32. SambridgeM.1999. Geophysical inversion with a neighbourhood algorithm searching a parameter space. Journal of Geophysical Research, 1999, 103, 4839–4878.
    [Google Scholar]
  33. SavvaidisA., OhrnbergerM., WatheletM., CornouC., BardP.‐Y. and TheodoulidisN.2009. Variability Analysis of Shallow Shear Wave Velocity Profiles Obtained from Dispersion Curve Inversion considering Multiple Model Parameterizations. SSA meeting, Poster#54, Monterey, USA.
    [Google Scholar]
  34. SoccoL. V. and StrobbiaC.2004. Surface‐wave method for near‐surface characterization: A tutorial. Near Surface Geophysics, 2004, 165–185.
    [Google Scholar]
  35. TokimatsuK., TamuraS. and KojimaH.1992. Effects of multiple modes on Rayleigh wave dispersion characteristics. Journal of Geotechnical Engineering118, 1529–1543.
    [Google Scholar]
  36. WatheletM.2008. An improved neighbourhood algorithm: Parameter conditions and dynamic scaling. Geophysical Research Letters 35, L09301. doi: 10.1029/2008GL033256.
    [Google Scholar]
  37. WatheletM., JongmansD., and OhrnbergerM.2004. Surface wave inversion using a direct search algorithm and its application to ambient vibration measurements. Near Surface Geophysics2, 211–221.
    [Google Scholar]
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