Technical Papers
Nov 23, 2021

Modeling Nonstationary Non-Gaussian Hurricane Wind Velocity and Gust Factor

Publication: Journal of Structural Engineering
Volume 148, Issue 2

Abstract

This study estimated the wind gust factor and turbulence intensity for hurricane winds that are modeled as a nonstationary non-Gaussian process. The estimation considered the time-varying mean wind velocity, and the time–frequency decomposition using S-transform characterized the time-varying amplitude and frequency content of the fluctuating wind. Winds simulated by applying a newly developed algorithm were used to augment the sample size. Results indicate that the standardized power spectral density function of hurricane winds can be represented in terms of the reduced frequency but with time-varying mean wind velocity. The standardized fluctuating wind is only weakly non-Gaussian; the average skewness and kurtosis coefficients are not very sensitive to whether the 10-or 60-min time-varying mean wind speed is considered. The assessed relation between the gust factor and turbulence intensity indicates that such a relationship is influenced by whether the instantaneous aspect of the nonstationary process is considered. There is large uncertainty in the developed relationship. By removing samples associated with a low mean wind velocity, the largest value of the estimated gust factor decreases. The consideration of the non-Gaussian aspect of the fluctuating wind to estimate the gust factor could be important as turbulence intensity increases.

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Data Availability Statement

Some or all data, models or code generated or used during the study are available from the corresponding author by request. These include all the obtained samples of turbulence intensity and gust factors, and the estimated power spectral density function.

Acknowledgments

Financial support received from the Natural Sciences and Engineering Research Council of Canada (RGPIN-2016-04814, for the second author), the University of Western Ontario, and the China Scholarship Council (No. 201807980004, for the first author) is gratefully acknowledged. The authors thank F. Masters for providing the wind hurricane wind records.

References

Balderrama, J. A., F. J. Masters, and K. R. Gurley. 2012. “Peak factor estimation in hurricane surface winds.” J. Wind Eng. Ind. Aerodyn. 102 (5): 1–13. https://doi.org/10.1016/j.jweia.2011.12.003.
Balderrama, J. A., F. J. Masters, K. R. Gurley, D. O. Prevatt, L. D. Aponte-Bermudez, T. A. Reinhold, J.-P. Pinelli, C. S. Subramanian, S. D. Schiff, and A. G. Chowdhury. 2011. “The Florida coastal monitoring program (FCMP): A review.” J. Wind Eng. Ind. Aerodyn. 99 (9): 979–995. https://doi.org/10.1016/j.jweia.2011.07.002.
Bendat, J. S., and A. G. Piersol. 2011. Random data: Analysis and measurement procedures. New York: Wiley.
Cao, S., Y. Tamura, N. Kikuchi, M. Saito, I. Nakayama, and Y. Matsuzaki. 2009. “Wind characteristics of a strong typhoon.” J. Wind Eng. Ind. Aerodyn. 97 (1): 11–21. https://doi.org/10.1016/j.jweia.2008.10.002.
Chen, J., M. C. Hui, and Y. L. Xu. 2007. “A comparative study of stationary and non-stationary wind models using field measurements.” Boundary Layer Meteorol. 122 (1): 105–121. https://doi.org/10.1007/s10546-006-9085-1.
Choi, E. C. C. 1983. “Gradient height and velocity profile during typhoons.” J. Wind Eng. Ind. Aerodyn. 13 (Apr): 31–41. https://doi.org/10.1016/0167-6105(83)90126-5.
Cook, N. J. 1985. The designer’s guide to wind loading on building structures. Part I: Background, damage survey, wind data, and structural classification. Watford, UK: Building Research Establishment.
Daubechies, I. 1992. Ten lectures on wavelets. New York: Siam.
Davenport, A. G. 1964. “Note on the distribution of the largest value of a random function with application to gust loading.” Proc. Inst. Civ. Eng. 28 (Jan): 187–196. https://doi.org/10.1680/iicep.1964.10112.
Durst, C. S. 1960. “Wind speeds over short periods of time.” Meteorol. Mag. 89 (1056): 181–186.
Florida Coastal Monitoring Program. 2002. “Tower deployment—Lili.” Accessed March 1, 2021. https://fcmp.ce.ufl.edu/collected-data-index/lili/tower-deployment-lili/.
Hong, H. P. 2016. “Modeling of nonstationary winds and its applications.” J. Eng. Mech. 142 (4): 04016004. https://doi.org/10.1061/(ASCE)EM.1943-7889.0001047.
Hong, H. P. 2021. “Response and first passage probability of linear elastic SDOF systems subjected to nonstationary stochastic excitation modelled through S-transform” Struct. Saf. 88 (20): 102007. https://doi.org/10.1016/j.strusafe.2020.102007.
Hong, H. P., and X. Z. Cui. 2020. “Time-frequency spectral representation models to simulate nonstationary processes and their use to generate ground motions.” J. Eng. Mech. 146 (9): 04020106. https://doi.org/10.1061/(asce)em.1943-7889.0001827.
Hong, H. P., X. Z. Cui, and D. Qiao. 2021a. “An algorithm to simulate nonstationary and non-Gaussian stochastic processes.” J. Infrastruct. Preserv. Resilience 2 (1): 1–15. https://doi.org/10.1186/s43065-021-00030-5.
Hong, H. P., X. Z. Cui, and M. Y. Xiao. 2021b. “Modelling and simulating thunderstorm /downburst winds using S-transform and discrete orthonormal S-transform.” J. Wind Eng. Ind. Aerodyn. 212 (Apr): 104598. https://doi.org/10.1016/j.jweia.2021.104598.
Hong, H. P., X. Z. Cui, and W. X. Zhou. 2021c. “A model to simulate multidimensional nonstationary and non-Gaussian fields based on S-transform.” Mech. Syst. Sig. Process. 159 (Oct): 107789. https://doi.org/10.1016/j.ymssp.2021.107789.
Huang, G., and X. Chen. 2009. “Wavelets-based estimation of multivariate evolutionary spectra and its application to nonstationary downburst winds.” Eng. Struct. 31 (4): 976–989. https://doi.org/10.1016/j.engstruct.2008.12.010.
Huang, G., H. Zheng, Y.-L. Xu, and Y. Li. 2015. “Spectrum models for nonstationary extreme winds.” J. Struct. Eng. 141 (10): 04015010. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001257.
Huang, N. E., Z. Shen, S. R. Long, M. C. Wu, H. H. Shih, and Q. Zheng. 1998. “The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis.” Proc. R. Soc. London 454 (1971): 903–995.
Huang, P., W. Xie, and M. Gu. 2020a. “A comparative study of the wind characteristics of three typhoons based on stationary and nonstationary models.” Nat. Hazards 101 (3): 785–815. https://doi.org/10.1007/s11069-020-03894-0.
Huang, Z., and M. Gu. 2019. “Estimation of peak factor and gust factor of nonstationary wind speed.” J. Wind Eng. Ind. Aerodyn. 193 (Sep): 103953. https://doi.org/10.1016/j.jweia.2019.103953.
Huang, Z., Y. L. Xu, T. Tao, and S. Zhan. 2020b. “Time-varying power spectra and coherences of non-stationary typhoon winds.” J. Wind Eng. Indus. Aerodyn. 198 (Mar): 104115. https://doi.org/10.1016/j.jweia.2020.104115.
Ishizaki, H. 1983. “Wind profiles, turbulence intensities and gust factors for design in typhoon-prone regions.” J. Wind Eng. Ind. Aerodyn. 13 (1–3): 55–66. https://doi.org/10.1016/0167-6105(83)90128-9.
Kareem, A., and J. Zhao. 1994. “Analysis of non-Gaussian surge response of tension leg platforms under wind loads.” J. Offshore Mech. Arct. Eng. 116 (3): 137–144. https://doi.org/10.1115/1.2920142.
Li, L., A. Kareem, J. Hunt, Y. Xiao, C. Zhou, and L. Song. 2015a. “Turbulence spectra for boundary-layer winds in tropical cyclones: a conceptual framework and field measurements at coastlines.” Bound.-Layer Meteorol. 154 (2): 243–263. https://doi.org/10.1007/s10546-014-9974-7.
Li, L., A. Kareem, Y. Xiao, L. Song, and C. Zhou. 2015b. “A comparative study of field measurements of the turbulence characteristics of typhoon and hurricane winds.” J. Wind Eng. Ind. Aerodyn. 140 (May): 49–66. https://doi.org/10.1016/j.jweia.2014.12.008.
Li, L., Y. Xiao, A. Kareem, L. Song, and P. Qin. 2012. “Modeling typhoon wind power spectra near sea surface based on measurements in the South China sea.” J. Wind Eng. Ind. Aerodyn. 104 (May): 565–576. https://doi.org/10.1016/j.jweia.2012.04.005.
Li, Q. S., and J. R. Wu. 2007. “Time–frequency analysis of typhoon effects on a 79-storey tall building.” J. Wind Eng. Ind. Aerodyn. 95 (12): 1648–1666. https://doi.org/10.1016/j.jweia.2007.02.030.
Lombardo, F. T., D. A. Smith, J. L. Schroeder, and K. C. Mehta. 2014. “Thunderstorm characteristics of importance to wind engineering.” J. Wind Eng. Ind. Aerodyn. 125 (Feb): 121–132. https://doi.org/10.1016/j.jweia.2013.12.004.
Masters, F. J., and K. R. Gurley. 2003. “Non-Gaussian simulation: cumulative distribution function map-based spectral correction.” J. Eng. Mech. 129 (12): 1418–1428. https://doi.org/10.1061/(ASCE)0733-9399(2003)129:12(1418).
Miller, C., J. A. Balderrama, and F. J. Masters. 2015. “Aspects of observed gust factors in landfalling tropical cyclones: Gust components, terrain, and upstream fetch effects.” Bound.-Layer Meteorol. 155 (1): 129–155. https://doi.org/10.1007/s10546-014-9989-0.
Newland, D. E. 1994. “Wavelet analysis of vibration, Part I: Theory.” J. Vib. Acoust. 38: 409–416. https://doi.org/10.1115/1.2930443.
Olesen, H. R., S. E. Larsen, and J. Højstrup. 1984. “Modelling velocity spectra in the lower part of the planetary boundary layer.” Bound.-Layer Meteorol. 29 (3): 285–312. https://doi.org/10.1007/BF00119794.
Peng, L., G. Huang, X. Chen, and Q. Yang. 2018. “Evolutionary spectra-based time-varying coherence function and application in structural response analysis to downburst winds.” J. Struct. Eng. 144 (7): 04018078. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002066.
Percival, D. B., and A. T. Walden. 2000. Wavelet methods for time series analysis. Cambridge, UK: Cambridge University Press.
Pickands, J., III. 1975. “Statistical inference using extreme order statistics.” Ann. Stat. 3 (1): 119–131. https://doi.org/10.1214/aos/1176343003.
Priestley, M. B. 1965. “Evolutionary spectra and non-stationary processes.” J. R. Statis. Soc.: Series B (Methodological) 27 (2): 204–229. https://doi.org/10.1111/j.2517-6161.1965.tb01488.x.
Schreiber, T., and A. Schmitz. 1996. “Improved surrogate data for nonlinearity tests.” Phys. Rev. Lett. 77 (4): 635. https://doi.org/10.1103/PhysRevLett.77.635.
Simiu, E., and R. H. Scanlan. 1996. Wind effects on structures—Fundamentals and applications to design. New York: Wiley.
Spanos, P. D., and G. Failla. 2004. “Evolutionary spectra estimation using wavelets.” J. Eng. Mech. 130 (8): 952–960. https://doi.org/10.1061/(ASCE)0733-9399(2004)130:8(952).
Stockwell, R. G., L. Mansinha, and R. P. Lowe. 1996. “Localization of the complex spectrum: the S transform.” IEEE Trans. Signal Process. 44 (4): 998–1001. https://doi.org/10.1109/78.492555.
Suomi, I., and T. Vihma. 2018. “Wind gust measurement techniques—From traditional anemometry to new possibilities.” Sensors 18 (4): 1300. https://doi.org/10.3390/s18041300.
Tao, T., H. Wang, and T. Wu. 2017. “Comparative study of the wind characteristics of a strong wind event based on stationary and nonstationary models.” J. Struct. Eng. 143 (5): 04016230. https://doi.org/10.1061/(ASCE)ST.1943-541X.0001725.
Tubino, F., and G. Solari. 2020. “Time varying mean extraction for stationary and nonstationary winds.” J. Wind Eng. Ind. Aerodyn. 203 (1): 104187. https://doi.org/10.1016/j.jweia.2020.104187.
Vanmarcke, E. H. 1976. “Structural response to earthquakes.” In Developments in geotechnical engineering, 287–337. New York: Elsevier.
Wang, H., T. Wu, T. Tao, A. Li, and A. Kareem. 2016. “Measurements and analysis of non-stationary wind characteristics at Sutong Bridge in Typhoon Damrey.” J. Wind Eng. Ind. Aerodyn. 151 (Jan): 100–106. https://doi.org/10.1016/j.jweia.2016.02.001.
Wang, H., Z. Xu, T. Wu, and J. Mao. 2018. “Evolutionary power spectral density of recorded typhoons at Sutong Bridge using harmonic wavelets.” J. Wind Eng. Ind. Aerodyn. 177 (Sep): 197–212. https://doi.org/10.1016/j.jweia.2018.04.015.
Wang, L., and A. Kareem. 2004. “Modeling of non-stationary winds in gust-fronts.” In Proc., 9th ASCE Specialty Conf. on Probabilistic Mechanics and Structural Reliability, 1–6. New York: Curran Associates.
Winterstein, S. R. 1988. “Nonlinear vibration models for extremes and fatigue.” J. Eng. Mech. 114 (10): 1772–1790. https://doi.org/10.1061/(asce)0733-9399(1988)114:10(1772).
Xu, Y. L., and J. Chen. 2004. “Characterizing nonstationary wind speed using empirical mode decomposition.” J. Struct. Eng. 130 (6): 912–920. https://doi.org/10.1061/(ASCE)0733-9445(2004)130:6(912).
Yu, B., A. G. Chowdhury, and F. J. Masters. 2008. “Hurricane wind power spectra, cospectra, and integral length scales.” Boundary-layer Meteorol. 129 (3): 411–430. https://doi.org/10.1007/s10546-008-9316-8.
Zhao, H., M. Grigoriu, and K. R. Gurley. 2019. “Translation processes for wind pressures on low-rise buildings.” J. Wind Eng. Ind. Aerodyn. 184 (5): 405–416. https://doi.org/10.1016/j.jweia.2018.12.007.

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Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 148Issue 2February 2022

History

Received: May 25, 2021
Accepted: Sep 20, 2021
Published online: Nov 23, 2021
Published in print: Feb 1, 2022
Discussion open until: Apr 23, 2022

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Ph.D. Candidate, Dept. of Civil and Environmental Engineering, Univ. of Western Ontario, London, Canada N6A 5B9. Email: [email protected]
Professor, Dept. of Civil and Environmental Engineering, Univ. of Western Ontario, London, Canada N6A 5B9 (corresponding author). ORCID: https://orcid.org/0000-0002-6959-2409. Email: [email protected]

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