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Improved first-order method for estimating extreme wind pressure considering directionality for non-typhoon climates

  • Wang, Jingcheng (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University) ;
  • Quan, Yong (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University) ;
  • Gu, Ming (State Key Laboratory of Disaster Reduction in Civil Engineering, Tongji University)
  • Received : 2019.01.16
  • Accepted : 2020.11.21
  • Published : 2020.11.25

Abstract

The first-order method for estimating the extreme wind pressure on building envelopes with consideration of the directionality of wind speed and wind pressure is improved to enhance its computational efficiency. In this improved method, the result is obtained directly from the empirical distribution of a random selection of annual maximum wind pressure samples generated by a Monte Carlo method, rather than from the previously utilized extreme wind pressure probability distribution. A discussion of the relationship between the first- and full-order methods indicates that when extreme wind pressures in a non-typhoon climate with a high return period are estimated with consideration of directionality, using the relatively simple first-order method instead of the computationally intensive full-order method is reasonable. The validation of this reasonableness is equivalent to validating two assumptions to improve its computational efficiency: 1) The result obtained by the full-order method is conservative when the extreme wind pressure events among different sectors are independent. 2) The result obtained by the first-order method for a high return period is not significantly affected when the extreme wind speeds among the different sectors are assumed to be independent. These two assumptions are validated by examples in different regions and theoretical derivation.

Keywords

Acknowledgement

The present study is jointly supported by the National Natural Science Foundation (No. 51778493) and the State Key Laboratory of Disaster Reduction in Civil Engineering (Grant No. SLDRCE19-B-13), which are both gratefully acknowledged.

References

  1. Chen, X.Z. and Huang, G.Q. (2010), "Estimation of probabilistic extreme wind load effects: Combination of aerodynamic and wind climate data", J. Eng. Mech., 136(6), 747-760. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000118.
  2. Coles, S., Bawa, J., Trenner, L. and Dorazio, P. (2001), An introduction to statistical modeling of extreme values (Vol. 208), Springer, London, U.K.
  3. Cook, N.J. and Harris, R.I. (2004), "Exact and general FT1 penultimate distributions of extreme wind speeds drawn from tail-equivalent Weibull parents", Struct. Saf., 26(4), 391-420. https://doi.org/10.1016/j.strusafe.2004.01.002.
  4. Cook, N.J. and Mayne, J.R. (1979), "A novel working approach to the assessment of wind loads for equivalent static design", J. Wind Eng. Ind. Aerod., 4(2), 149-164. https://doi.org/10.1016/0167-6105(79)90043-6.
  5. Cook, N.J. and Mayne, J.R. (1980), "A refined working approach to the assessment of wind loads for equivalent static design", J. Wind Eng. Ind. Aerod., 6(1-2), 125-137. https://doi.org/10.1016/0167-6105(80)90026-4.
  6. Embrechts, P., Lindskog, F. and McNeil, A. (2001), "Modelling dependence with copulas and applications to risk management", Rapport technique; Departement de mathematiques, Institut Federal de Technologie de Zurich, Zurich, Switzerland.
  7. Gabbai, R.D. and Simiu, E. (2014), "Evaluation of mean recurrence intervals of wind effects for tall building design", J. Struct. Eng., 140(1), 04013037. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000818.
  8. Gavanski, E. and Cook, N.J. (2019), "Evaluation of XIMIS for assessing extreme pressure coefficients", Front Built Environ, 5, 48. https://doi.org/10.3389/fbuil.2019.00048.
  9. Genest, C. and Favre, A.C. (2007), "Everything you always wanted to know about copula modeling but were afraid to ask", J. Hydrol. Eng., 12(4), 347-368. https://doi.org/10.1061/(ASCE)1084-0699(2007)12:4(347).
  10. Grigoriu, M. (2007), "Multivariate distributions with specified marginals: Applications to Wind Engineering", J. Eng. Mech., 133(2), 174-184. https://doi.org/10.1061/(ASCE)0733-9399(2007)133:2(174).
  11. Gumley, S. and Wood, C. (1982), "A discussion of extreme windloading probabilities", J. Wind Eng. Ind. Aerod., 10(1), 31-45. https://doi.org/10.1016/0167-6105(82)90052-6.
  12. Harris, R.I. (1982), "An improved method for the prediction of extreme values of wind effects on simple buildings and structures", J. Wind Eng. Ind. Aerod., 9(3), 343-379. https://doi.org/10.1016/0167-6105(82)90023-X.
  13. Harris, R.I. (2005), "A new direct version of the Cook-Mayne method for wind pressure probabilities in temperate storms", J Wind Eng. Ind. Aerod., 93(7), 581-600. https://doi.org/10.1016/j.jweia.2005.05.004.
  14. Harris, R.I. (2014), "A simulation method for the macrometeorological wind speed and the implications for extreme value analysis", J. Wind Eng. Ind. Aerod., 125, 146-155. https://doi.org/10.1016/j.jweia.2013.12.003.
  15. Holmes, J.D. (2015), Wind loading of structures, CRC press, Boca Raton, Florida, U.S.A.
  16. Isyumov, N., Mikitiuk, M.J., Case, P.C., Lythe, G.R. and Welburn, A. (2003), "Predictions of wind loads and responses from simulated tropical storm passages", Proceedings of the 11th international Conference on Wind Engineering, Lubbock, Texas, U.S.A., June.
  17. Isyumov, N., Ho, E. and Case, P. (2014), "Influence of wind directionality on wind loads and responses", J. Wind Eng. Ind. Aerod., 133, 169-180. https://doi.org/10.1016/j.jweia.2014.06.006.
  18. Kottegoda, N.T. and Rosso, R. (2008), Applied statistics for civil and environmental engineers. Second Edition, Blackwell Publishing, Hoboken, New Jersey, U.S.A.
  19. Luo, Y., Huang, G. (2019), "Extreme wind load on structures based on full-order method considering directionality", Proceedings of 19th China Conference on Wind Engineering, Xiamen, Fujian, China, April.
  20. Nikoloulopoulos, A.K., Joe, H., and Li, H. (2009), "Extreme value properties of multivariate t Copulas", Extremes, 12(2), 129-148. http://dx.doi.org/10.1007/s10687-008-0072-4.
  21. Quan, Y., Gu, M., Tamura, Y. and Chen, B. (2009), "An extrem-evalue estimating method of non-Gaussian wind pressure", Proceedings of Seventh Asia-Pacific Conference on Wind Engineering (APCWE-VII), Taipei, Taiwan, China, November.
  22. Quan, Y., Wang, J.C. and Gu, M. (2017), "A joint probability distribution model of directional extreme wind speeds based on the t-Copula function", Wind Struct., 25(3), 261-282. https://doi.org/10.12989/was.2017.25.3.261.
  23. Salvadori, G., De Michele, C., Kottegoda, N.T., and Rosso, R. (2007), Extremes in nature: an approach using copulas, Springer Science & Business Media, Berlin, Germany.
  24. Simiu, E. and Yeo, D.H. (2015), "Advances in the design of high-rise structures by the wind tunnel procedure: Conceptual framework", Wind Struct., 21(5), 489-503. https://doi.org/10.12989/was.2015.21.5.489.
  25. Tian, J., Chen, X. (2020). "Evaluation of wind directionality on wind load effects and assessment of system reliability of wind-excited structures", J. Wind Eng. Ind. Aerod., 199, 104133. https://doi.org/10.1016/j.jweia.2020.104133
  26. Torrielli, A., Repetto, M.P. and Solari, G. (2013), "Extreme wind speeds from long-term synthetic records", J. Wind Eng. Ind. Aerod., 115(2), 22-38. https://doi.org/10.1016/j.jweia.2012.12.008.
  27. Yeo, D.H. and Simiu,E. (2011), "High-rise reinforced concrete structures: Database-assisted design for wind", J. Struct. Eng., 137(11), 1340-1349. https://doi.org/10.1061/(ASCE)ST.1943-541X.0000394.
  28. Zhang, X.X. and Chen, X.Z. (2015), "Assessing probabilistic wind load effects via a multivariate extreme wind speed model: A unified framework to consider directionality and uncertainty", J. Wind Eng. Ind. Aerod., 147(2015), 30-42. https://doi.org/10.1016/j.jweia.2015.09.002.
  29. Zhang, X.X. and Chen, X.Z. (2016), "Influence of dependence of directional extreme wind speeds on wind load effects with various mean recurrence intervals", J. Wind Eng. Ind. Aerod., 148(2016), 45-56. https://doi.org/10.1016/j.jweia.2015.11.005.