Earthquakes and Structures

  • 제16권5호
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  • Pages.563-573
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  • 2019
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  • 2092-7614(pISSN)
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  • 2092-7622(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Simulation method of ground motion matching for multiple targets and effects of fitting parameter variation on the distribution of PGD

  • Wang, Shaoqing (Institute of Geophysics, China Earthquake Administration) ;
  • Yu, Ruifang (Institute of Geophysics, China Earthquake Administration) ;
  • Li, Xiaojun (Institute of Geophysics, China Earthquake Administration) ;
  • Lv, Hongshan (Institute of Geophysics, China Earthquake Administration)
  • 투고 : 2018.10.04
  • 심사 : 2019.03.28
  • 발행 : 2019.05.25
⟨ 이전 논문 다음 논문 ⟩

초록

When generating spectrum-compatible artificial ground motion in engineering practices, the effect of the variation in fitting parameters on the distribution of the peak ground displacement (PGD) has not yet drawn enough attention. In this study, a method for simulating ground motion matching for multiple targets is developed. In this method, a frequency-dependent amplitude envelope function with statistical parameters is introduced to simulate the nonstationarity of the frequency in earthquake ground motion. Then, several groups of time-history acceleration with different temporal and spectral nonstationarities were generated to analyze the effect of nonstationary parameter variations on the distribution of PGD. The following conclusions are drawn from the results: (1) In the simulation of spectrum-compatible artificial ground motion, if the acceleration time-history is generated with random initial phases, the corresponding PGD distribution is quite discrete and an uncertain number of PGD values lower than the limit value are observed. Nevertheless, the mean values of PGD always meet the requirement in every group. (2) If the nonstationary frequencies of the ground motion are taken into account when fitting the target spectrum, the corresponding PGD values will increase. A correlation analysis shows that the change in the mean and the dispersion values, from before the frequencies are controlled to after, correlates with the modal parameters of the predominant frequencies. (3) Extending the maximum period of the target spectrum will increase the corresponding PGD value and, simultaneously, decrease the PGD dispersion. Finally, in order to control the PGD effectively, the ground motion simulation method suggested in this study was revised to target a specified PGD. This novel method can generate ground motion that satisfies not only the required precision of the target spectrum, peak ground acceleration (PGA), and nonstationarity characteristics of the ground motion but also meets the required limit of the PGD, improving engineering practices.

키워드

과제정보

연구 과제 주관 기관 : Natural Science Foundation of China

참고문헌

  1. Amin, M. and Ang A.H.S (1968), "Nonstationary stochastic models of earthquake motions", J. Eng. Mech., ASCE, 94(2), 559-584.
  2. Boashash, B. (1992a), "Estimating and interpreting the instantaneous frequency of a signal-part 1: Fundamentals", Proc. IEEE, 80(4), 520-538. https://doi.org/10.1109/5.135376.
  3. Boashash, B. (1992b), "Estimating and interpreting the instantaneous frequency of a signal-part 2: Algorithms and applications", Proc. IEEE, 80(4), 540-568. https://doi.org/10.1109/5.135378
  4. Boore, M.D. (2005), "On pads and filters: processing strongmotion data", Bull. Seismol. Soc. Am., 95(2), 745-750. https://doi.org/10.1785/0120040160.
  5. Buratti, N. and Tavano, M. (2014), "Dynamic buckling and seismic fragility of anchored steel tanks by the added mass method", Earthq. Eng Struct. Dyn., 43, 1-21. https://doi.org/10.1002/eqe.2326.
  6. Cacciola, P. (2010), "A stochastic approach for generating spectrum compatible fully nonstationary earthquakes", Comput. Struct., 88(15-16), 889-901. https://doi.org/10.1016/j.compstruc.2010.04.009.
  7. Carballo, J.E. and Cornell, C.A. (2000), "Probabilistic seismic demand analysis: Spectrum matching and design", Report No. RMS-41, Department of Civil and Environmental Engineering, Stanford University.
  8. Castagna, J.P., Sun, S.J. and Siegfried R.W. (2003), "Instantaneous spectral analysis: detection of low-frequency shadows associated with hydrocarbons", Lead. Edge, 22(2), 120-127. https://doi.org/10.1190/1.1559038.
  9. Clough R.W. and Penzien J. (1975), Dynamics of Structures, McGraw-Hill, New York U.S.A.
  10. Converse, M.A. and Brady, G.A. (1992), "BAP: Basic Strong-Motion Accelerogram Processing Software: Version 1.0," Open- File Report 92-296A, United States Department of The Interior U.S. Geological Survey.
  11. Gao, Y.F., Wu, Y.X., Li, D.Y., Zhang, N. and Zhang, F. (2014), "An improved method for the generating of spectrumcompatible time series using wavelets", Earthq. Spectra, 30(4), 1467-1485. https://doi.org/10.1193/051912EQS190M.
  12. GB50909-2014 (2014), Code for Seismic Design of Urban Rail Transit, Ministry of Construction of People's Republic of China, Beijing, China. (in Chinese)
  13. Ghaboussi, J. and Lin, C.J. (1998), "New method of generating spectrum compatible accelerograms using neural networks", Earthq. Eng. Struct. Dyn., 27, 377-396. https://doi.org/10.1002/(SICI)1096-9845(199804)27:4<377.
  14. Guan, M.S., Du, H.B., Cui, J., Zeng, Q.L. and Jiang, H.B. (2015), "Optimal ground motion intensity measure for long-period structures", Measure. Sci. Technol., 26(10), 105001. https://doi.org/10.1088/0957-0233/26/10/105001
  15. Hall, J.F., Heaton, T.H., Halling, M.W. and Wald, D.J. (1995), "Near-source ground motion and its effects on flexible buildings", Earthq. Spectra, 11(4), 569-605. https://doi.org/10.1193/1.1585828.
  16. Han, M., Duan, Y.L., Sun, H. and Sheng, W. (2013), "Influence of characteristics parameters of near-fault ground motions on the seismic responses of base-isolated structures", China Civil Eng. J., 46(6), 8-13. (in Chinese)
  17. Hancock, J., Watson-Lamprey, J., Abrahamson, N.A., Bommer, J.J., Markatis, A., McCOTH, E. and Mendis, R. (2006), "An improved method of matching response spectra of recorded earthquake ground motion using wavelets", J. Earthq. Eng., 10(S1), 67-89.
  18. Huang, N.E., Shen, Z., Long, S.R., Wu, M.C., Shin, H.H., Zheng, Q., Yen, N.C., Tung, C.C. and Liu, H.H. (1998), "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis", Proc. R. Soc. Lond. A, 454(1971), 903-995. https://doi.org/10.1098/rspa.1998.0193.
  19. Iwan, W.D., Moser, M.A. and Peng, C.Y. (1985), "Some observations on strong-motion earthquake measurement using a digital accelerograph", Bull. Seismol. Soc. Am., 75(5), 1225-1246. https://doi.org/10.1785/BSSA0750051225
  20. Iyengar, R.N. and Iyengar, K.T.S.R. (1969), "A nonstationary random process model for earthquake accelerograms", Bull. Seismol. Soc. Am., 59(3), 1163-1188.
  21. Lilhanand K. and Tseng W.S. (1988), "Development and application of realistic earthquake time histories compatible with multiple-damping design spectra", Proceedings of Ninth World Conference on Earthquake Engineering, Tokyo, August.
  22. Milana, G., Rovelli, A., Sortis, A.D., Calderoni, G., Coco, G., Corrao, M. and Marsan, P. (2008), "The role of long-period ground motions on magnitude and damage of volcanic earthquakes on Mt. Etna, Italy", Bull. Seismol. Soc. Am., 98(6), 2724-2738. https://doi.org/10.1785/0120080072.
  23. Mukherjee, S. and Gupta, V.K. (2002) "Wavelet-based generation of spectrum-compatible time-histories", Soil Dyn. Earthq. Eng., 22, 799-804. https://doi.org/10.1016/S0267-7261(02)00101-X.
  24. Naeim, F. and Lew, M. (1995), "On the use of design spectrum compatible time histories", Earthq. Spectra, 11(1), 111-127. https://doi.org/10.1193/1.1585805.
  25. Newland, D.E. (1994), "Wavelet analysis of vibration: Part 2- wavelet maps", J. Vib. Acoust., 116(4), 417-425. https://doi.org/10.1115/1.2930444.
  26. Nigam, N.C. and Mark, W.D. (1984). "Introduction to random vibrations", J. Acoust. Soc. Am., 76(6), 1871. https://doi.org/10.1121/1.391500.
  27. Pineda-Porras, O. and Ordaz, M. (2007), "A new seismic intensity parameter to estimate damage in buried pipelines due to seismic wave propagation", J. Earthq. Eng., 11(5), 773-786. https://doi.org/10.1080/13632460701242781.
  28. Preumont, A. (1984), "The generation of spectrum compatible accelerograms for the design of nuclear power plants", Earthq. Eng. Struct. Dyn., 12(4), 481-497. https://doi.org/10.1002/eqe.4290120405.
  29. Rezaeian, S. and Kiureghian, A.D. (2008). "A stochastic ground motion model with separable temporal and spectral nonstationarities", Earthq. Eng Struct. Dyn., 37, 1565-1584. https://doi.org/10.1002/eqe.831.
  30. Rezaeian, S. and Kiureghian, A.D. (2010), "Simulation of synthetic ground motions for specified earthquake and site characteristics", Earthq. Eng Struct. Dyn., 39, 1155-1180. https://doi.org/10.1002/eqe.997.
  31. Tondini, N. and Stojadinovic, B. (2012), "Probabilistic seismic demand model for curved reinforced concrete bridges", Bull. Earthq. Eng., 10, 1455-1479. https://doi.org/10.1007/s10518-012-9362-y.
  32. Yu, R.F., Yuan, M.Q. and Yu, Y.X., (2015), "Developed empirical model for simulation of time-varying frequency in earthquake ground motion", Earthq. Struct., 8(6), 1463-1480. http://dx.doi.org/10.12989/eas.2015.8.6.1463.
  33. Zhao, F.X., Zhang, Y.S. and Lu, H.S. (2006), "Artificial ground motion compatible with specified ground shaking peaks and target response spectrum", Earthq. Eng. Eng. Vib., 5, 41-48. https://doi.org/10.1007/s11803-006-0625-y.

피인용 문헌

  1. Assessment of seismic risk of a typical RC building for the 2016 Gyeongju and potential earthquakes vol.20, pp.3, 2019, https://doi.org/10.12989/eas.2021.20.3.337