Structural Engineering and Mechanics

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New method for generation of artificial ground motion by a nonstationary Kanai-Tajimi model and wavelet transform

  • Amiri, G. Ghodrati (Center of Excellence for Fundamental Studies in Structural Engineering, College of Civil Engineering, Iran University of Science & Technology) ;
  • Bagheri, A. (Center of Excellence for Fundamental Studies in Structural Engineering, College of Civil Engineering, Iran University of Science & Technology) ;
  • Fadavi, M. (Center of Excellence for Fundamental Studies in Structural Engineering, College of Civil Engineering, Iran University of Science & Technology)
  • Received : 2006.07.21
  • Accepted : 2007.03.22
  • Published : 2007.08.20
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Abstract

Considering the vast usage of time-history dynamic analyses to calculate structural responses and lack of sufficient and suitable earthquake records, generation of artificial accelerograms is very necessary. The main target of this paper is to present a novel method based on nonstationary Kanai-Tajimi model and wavelet transform to generate more artificial earthquake records, which are compatible with target spectrum. In this regard, the generalized nonstationary Kanai-Tajimi model to include the nonstationary evaluation of amplitude and dominant frequency of ground motion and properties of wavelet transform is used to generate ground acceleration time history. Application of the method for El Centro 1940 earthquake and two Iranian earthquakes (Tabas 1978 and Manjil 1990) is presented. It is shown that the model and identification algorithms are able to accurately capture the nonstationary features of these earthquake accelerograms. The statistical characteristics of the spectral response of the generated accelerograms are compared with those for the actual records to demonstrate the effectiveness of the method. Also, for comparison of the presented method with other methods, the response spectra of the synthetic accelerograms compared with the models of Fan and Ahmadi (1990) and Rofooei et al. (2001) and it is shown that the response spectra of the synthetic accelerograms with the method of this paper are close to those of actual earthquakes.

Keywords

References

  1. Ahmadi, G. (1979), 'Generation of artificial time-histories compatible with given response spectra - A review', SM Archives, 4, 207-239
  2. Daubechies, I. (1992), 'Ten Lectures on Wavelets', CBMS-NSF Conference Series in Applied Mathematics, Montpelier, Vermont
  3. Fan, F.G. and Ahmadi, G. (1990), 'Nonstationary Kanai-Tajimi models for El Centro 1940 and Mexico City 1985 earthquake', Prob. Eng. Mech., 5, 171-181 https://doi.org/10.1016/0266-8920(90)90018-F
  4. Ghodrati Amiri, G., Ashtari, P. and Rahami, H. (2006), 'New development of artificial record generation by wavelet theory', Struct. Eng. Mech., 22(2), 185-195 https://doi.org/10.12989/sem.2006.22.2.185
  5. Iyama, J. and Kuwamura, H. (1999), 'Application of wavelets to analysis and simulation of earthquake motions', Earthq. Eng. Struct. Dyn., 28, 255-272 https://doi.org/10.1002/(SICI)1096-9845(199903)28:3<255::AID-EQE815>3.0.CO;2-C
  6. Kanai, K. (1957), 'Semi-empirical formula for the seismic characteristics of the ground motion', Bull. Earth. Res. Inst. Univ. Tokyo, 35, 309-325
  7. MATLAB Reference Guide (1999), The Math Works Inc
  8. Mukherjee, S. and Gupta, K. (2002), 'Wavelet-based characterization of design ground motions', Earthq. Eng. Struct. Dyn., 31,1173-1190 https://doi.org/10.1002/eqe.155
  9. Naeim, F. (1999), The Seismic Design Handbook, Van Nostrand
  10. Newland, D.E. (1994), Random Vibrations, Spectral and Wavelet Analysis, 3rd Edition, Longman Singapore Publishers
  11. Refooei, F.R., Mobarake, A. and Ahmadi, G. (2001), 'Generation of artificial earthquake records with a nonstationary Kanai-Tajimi model', Eng. Struct., 23, 827-837 https://doi.org/10.1016/S0141-0296(00)00093-6
  12. Suarez, L.E. and Montejo, L.A. (2005), 'Generation of artificial earthquake via the wavelet transform', Solids Struct., 42, 5905-5919 https://doi.org/10.1016/j.ijsolstr.2005.03.025
  13. Tajimi, H. (1960), 'A statistical method of determining the maximum response of a building structure during an earthquake', In: Proc. 2nd WCEE, Vol. II. Tokyo: Science Council of Japan, 781-798
  14. Zhou, Z. and Adeli, H. (2003), 'Wavelet energy spectrum for time-frequency localization of earthquake energy', Comput. Aided Civil Infrastruct Eng., 13, 133-140

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