Structural Engineering and Mechanics

Techno-Press (테크노프레스)
권호 표지
DOI QR코드

DOI QR Code

Extraction of optimal time-varying mean of non-stationary wind speeds based on empirical mode decomposition

  • Cai, Kang (School of Civil and Hydraulic Engineering, Hefei University of Technology) ;
  • Li, Xiao (Architecture and Civil Engineering Research Center, City University of Hong Kong Shenzhen Research Institute) ;
  • Zhi, Lun-hai (School of Civil and Hydraulic Engineering, Hefei University of Technology) ;
  • Han, Xu-liang (Architecture and Civil Engineering Research Center, City University of Hong Kong Shenzhen Research Institute)
  • Received : 2020.08.02
  • Accepted : 2020.11.10
  • Published : 2021.02.10
⟨ Previous Next ⟩

Abstract

The time-varying mean (TVM) component of non-stationary wind speeds is commonly extracted utilizing empirical mode decomposition (EMD) in practice, whereas the accuracy of the extracted TVM is difficult to be quantified. To deal with this problem, this paper proposes an approach to identify and extract the optimal TVM from several TVM results obtained by the EMD. It is suggested that the optimal TVM of a 10-min time history of wind speeds should meet both the following conditions: (1) the probability density function (PDF) of fluctuating wind component agrees well with the modified Gaussian function (MGF). At this stage, a coefficient p is newly defined as an evaluation index to quantify the correlation between PDF and MGF. The smaller the p is, the better the derived TVM is; (2) the number of local maxima of obtained optimal TVM within a 10-min time interval is less than 6. The proposed approach is validated by a numerical example, and it is also adopted to extract the optimal TVM from the field measurement records of wind speeds collected during a sandstorm event.

Keywords

Acknowledgement

The work described in this paper was fully supported by grants from the National Natural Science Foundation of China (51478371 and 51978230), the Fundamental Research Funds for the Central Universities (PA2019GDZC0094). The financial support is gratefully acknowledged.

References

  1. AIJ-RLB (2004), Recommendations for loads on building-wind loads, Architectural Institute of Japan, Tokyo, Japan.
  2. ASCE/SE (2010), Minimum design loads for buildings and other structures, American Society of Civil Engineers, Reston, VA, USA.
  3. Chen, J, and Xu, Y.L. (2004), "On modelling of typhoon‐induced non‐stationary wind speed for tall buildings", Struct. Design Tall Special Buildings, 13, 145-163. https://doi.org/10.1002/tal.247.
  4. Chen, J., Hui, M.C.H. and Xu, Y.L. (2007), "A comparative study of stationary and non-stationary wind models using field measurements", Boundary-layer Meteorology, 122, 105-121. https://doi.org/10.1007/s10546-006-9085-1
  5. Chen, J. and Wu, M. (2012), "On extraction of time-varying mean wind speed from wind record based on stationarity index", Asia-Pacific J. Atmospheric Sci., 48, 315-323. https://doi.org/10.1007/s13143-012-0030-6.
  6. Chen, L., and Letchford, C.W. (2005), "Proper orthogonal decomposition of two vertical profiles of full-scale nonstationary downburst wind speeds[lzcl]", J. Wind Eng. Industrial Aerodynamics, 93, 187-216. https://doi.org/10.1016/j.jweia.2004.11.004.
  7. Choi, E.C.C., and Hidayat, F.A. (2002), "Dynamic response of structures to thunderstorm winds", Progress in Struct. Eng. Mater., 4, 408-416. https://doi.org/10.1002/pse.132
  8. Fragoulis, A. N. (1997), "The complex terrain wind environment and its effects on the power output and loading of wind turbines", Research Report No. A9715913, 35th Aerospace Sciences Meeting and Exhibit, 934. https://doi.org/10.2514/6.1997-934.
  9. GB50009 (2012), Load code for the design of building structures, China Architecture and Building Press, Beijing, China.
  10. Gil-Martin, L. M., Carbonell-Marquez, J. F., Hernandez-Montes, E., Aschheim, M. and Pasadas-Fernandez, M. (2012), "Dynamic magnification factors of SDOF oscillators under harmonic loading", Appl. Math. Lett., 25, 38-42. https://doi.org/10.1016/j.aml.2011.07.005
  11. Gong, Kuangmin, and Xinzhong Chen. (2014), "Influence of non-Gaussian wind characteristics on wind turbine extreme response", Eng. Struct., 59, 727-744. https://doi.org/10.1016/j.engstruct.2013.11.029.
  12. He, Y.C, Li, Q.S., Chan, P.W., Wu, J.R. and Fu, J.Y. (2019), "Toward modeling the spatial pressure field of tropical cyclones: insights from Typhoon Hato (1713)", J. Wind Eng. Industrial Aerodynam., 184, 378-390. https://doi.org/10.1016/j.jweia.2018.12.001
  13. Huang, G. and Chen, X. (2009), "Wavelets-based estimation of multivariate evolutionary spectra and its application to nonstationary downburst winds", Eng. Struct., 31, 976-989. https://doi.org/10.1016/j.engstruct.2008.12.010.
  14. Huang, Norden E, Zheng Shen, Steven R. Long, Manli C. Wu, Hsing H. Shih, Quanan Zheng, Nai-Chyuan Yen, Chi Chao Tung, and Henry H. Liu. (1998), "The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis", Proceedings of the Royal Society of London. Series A: Mathematical, Physical and Engineering Sciences, 454: 903-95. https://doi.org/10.1098/rspa.1998.0193
  15. Huang, P., Xie, W. and Gu, M. (2020), "A comparative study of the wind characteristics of three typhoons based on stationary and nonstationary models", Natural Hazards: J. Soc. Prevention Mitigation Natural Hazards, 101(3), 785-815. https://doi.org/10.1007/s11069-020-03894-0.
  16. Lixiao, Li., Kareem, A., Xiao, Y., Song, L. and Zhou, C. (2015), "A comparative study of field measurements of the turbulence characteristics of typhoon and hurricane winds", J. Wind Eng. Industrial Aerodynam., 140, 49-66. https://doi.org/10.1016/j.jweia.2014.12.008
  17. Li, L., Chen, K., Xia, D., Wang, H., Hu, H. and He, F. (2018), "Analysis on the wind characteristics under typhoon climate at the southeast coast of China", J. Wind Eng. Industrial Aerodynamics, 182, 37-48. https://doi.org/10.1016/j.jweia.2018.09.003
  18. Li, Q.S, Lunhai, Z. and Hu, F. (2010), "Boundary layer wind structure from observations on a 325 m tower", J. Wind Eng. Industrial Aerodynam., 98(12), 818-832. https://doi.org/10.1016/j.jweia.2010.08.001.
  19. Lombardo, F.T., Smith, D.A., Schroeder, J.L. and C. Mehta. (2014), "Thunderstorm characteristics of importance to wind engineering", J. Wind Eng. Industrial Aerodynam., 125, 121-32. https://doi.org/10.1016/j.jweia.2013.12.004.
  20. Mujtaba, Iqbal, M. and Macchietto, S. (1997), "Efficient optimization of batch distillation with chemical reaction using polynomial curve fitting techniques", Industrial Eng. Chemistry Research, 36(6), https://doi.org/10.1021/ie960573d.
  21. Rouillard, V. (2014), "Quantifying the Non‐stationarity of Vehicle Vibrations with the Run Test", Packaging Technol. Sci., 27(3), 203-219. https://doi.org/10.1002/pts.2024.
  22. Schulz, Eric, W, and Sanderson, B.G. (2004), "Stationarity of turbulence in light winds during the maritime continent thunderstorm experiment", Boundary-layer Meteorology, 111, 523-541. https://doi.org/10.1023/B:BOUN.0000016546.42602.0a.
  23. Su, Y., Huang, G. and Xu, Y. (2015), "Derivation of time-varying mean for non-stationary downburst winds", J. Wind Eng. Industrial Aerodynam., 141, 39-48. https://doi.org/10.1016/j.jweia.2015.02.008.
  24. Tian, Z,G. Wang, Y.R., Li, S. and Wang, Y. (2018), "An adaptive online sequential extreme learning machine for short-term wind speed prediction based on improved artificial bee colony algorithm", Neural Network World, 28(3), 191-212. http://doi.org/10.14311/NNW.2018.28.012
  25. Tian, Z., Wang, G., Li, S., Yanghong, W. and Wang, X. (2019), "Artificial bee colony algorithm- optimized error minimized extreme learning machine and its application in short-term wind speed prediction", Wind Eng., 43(3), 263-276. https://doi.org/10.1177/0309524X18780401,
  26. Wang, L., McCullough, M. and Kareem, A. (2013), "A data-driven approach for simulation of full-scale downburst wind speeds", J. Wind Eng. Industrial Aerodynam., 123, 171-90. https://doi.org/10.1016/j.jweia.2013.08.010
  27. Xu, Y. L., and Chen, J. (2004), "Characterizing nonstationary wind speed using empirical mode decomposition", J. Struct. Eng., 130, 912-920. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:6(912)