Wind and Structures

  • 제31권6호
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  • Pages.549-560
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  • 2020
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  • 1226-6116(pISSN)
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  • 1598-6225(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

DOI QR Code

Linear prediction and z-transform based CDF-mapping simulation algorithm of multivariate non-Gaussian fluctuating wind pressure

  • Jiang, Lei (School of civil engineering and architecture, Jiangsu University of science and technology) ;
  • Li, Chunxiang (Department of Civil Engineering, School of Mechanism and Engineering Science, Shanghai University) ;
  • Li, Jinhua (Department of Civil Engineering, East China Jiaotong University)
  • 투고 : 2020.06.07
  • 심사 : 2020.12.18
  • 발행 : 2020.12.25
⟨ 이전 논문 다음 논문 ⟩

초록

Methods for stochastic simulation of non-Gaussian wind pressure have increasingly addressed the efficiency and accuracy contents to offer an accurate description of the extreme value estimation of the long-span and high-rise structures. This paper presents a linear prediction and z-transform (LPZ) based Cumulative distribution function (CDF) mapping algorithm for the simulation of multivariate non-Gaussian fluctuating wind pressure. The new algorithm generates realizations of non-Gaussian with prescribed marginal probability distribution function (PDF) and prescribed spectral density function (PSD). The inverse linear prediction and z-transform function (ILPZ) is deduced. LPZ is improved and applied to non-Gaussian wind pressure simulation for the first time. The new algorithm is demonstrated to be efficient, flexible, and more accurate in comparison with the FFT-based method and Hermite polynomial model method in two examples for transverse softening and longitudinal hardening non-Gaussian wind pressures.

키워드

과제정보

This work was supported by the National Natural Science Foundation of China (No.51378304 and No. 51778354 and No.11962006). Also, the authors wish to thank Professor Zhi-hong Zhang for the precious wind pressure data for the flexible structure.

참고문헌

  1. Aly Mousaad Aly and Hamzeh Gol-Zaroudi (2020), "Peak pressures on low rise buildings: CFD with LES versus full scale and wind tunnel measurements", Wind Struct., 30(1), 99-117. https://doi.org/10.12989/was.2020.30.1.099.
  2. Aung, N.N., Ye, J. and Masters, F.J. (2012), "Simulation of multivariate non-Gaussian wind pressure on spherical latticed structures", Wind Struct., 15(3), 223-245. https://doi.org/10.12989/was.2012.15.3.223.
  3. Blaise, N., Canor, T. and Denoël, V. (2016), "Reconstruction of the envelope of non-Gaussian structural responses with principal static wind loads", Wind Eng. Ind. Aerod., 149, 59-76. https://doi.org/10.1016/j.jweia.2015.12.001.
  4. Deodatis, G. and Micaletti, R.C. (2001), "Simulation of highly skewed non-Gaussian stochastic processes", J. Eng. Mech., 127(12), 1284-1295. https://doi.org/10.1061/(ASCE)07339399(2001)127:12(1284).
  5. Ding, J. and Chen, X.Z. (2016), "Moment-based translation model for hardening non-Gaussian response processes", J. Eng. Mech., 142(2), 06015006. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000986.
  6. Fang, Z., Wang, Z. and Li, Z. (2020), "Prediction of downburst-induced wind pressure coefficients on high-rise building surfaces using BP neural network", Wind Struct., 30(3), 289-298. http://dx.doi.org/10.12989/was.2020.30.3.289.
  7. Gioffre, M., Gusella, V. and Grigoriu, M. (2000), "Simulation of non-Gaussian field applied to wind pressure fluctuations", Prob. Eng. Mech., 15(4), 339-345. https://doi.org/10.1016/S0266-8920(99)00035-1.
  8. Gong, K. and Chen, X. (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.
  9. Grigoriu, M. (1984), ''Crossing of non-Gaussian translation processes'', J. Eng. Mech., 110(4), 610-620. https://doi.org/10.1061/(ASCE)07339399(1984)110:4(610).
  10. Grigoriu, M. (1998), "Simulation of stationary non-Gaussian translation processes", J. Eng. Mech., 124(2), 121-126. https://doi.org/10.1061/(ASCE)0733-9399(1998)124:2(121).
  11. Gurley, K. and Kareem, A. (1997), "Analysis interpretation modeling and simulation of unsteady wind and pressure data", J. Wind Eng. Ind. Aerod., 69-71, 657-669. https://doi.org/10.1016/S0167-6105(97)00195-5.
  12. Gurley, K., Tognarelli, M. and Kareem, A. (1997), "Analysis and simulation tools for wind engineering", Prob. Eng. Mech., 12(1), 9-31. https://doi.org/10.1016/S0266-8920(96)00010-0.
  13. Gurley, K.R., Kareem, A. and Tognarelli M.A. (1996), "Simulation of a class of non-normal random processes", Int. J. Non-Linear Mech., 31(5), 601-617. https://doi.org/10.1016/0020-7462(96)00025-X.
  14. Huang, M.F., Lou, W., Pan, X., Chan, C.M. and Li, Q.S. (2014), "Hermite extreme value estimation of non-Gaussian wind load process on a long-span roof structure", J. Struct. Eng., 140(9), 04014061, https://doi.org/10.1061/(ASCE)ST.1943-541X.0000962.
  15. Jafari, M. and Sarkar Partha, P. (2020), "Wind tunnel study of wake-induced aerodynamics of parallel stay-cables and power conductor cables in a yawed flow", Wind Struct., 30(6), 617-631. https://doi.org/10.12989/was.2020.30.6.617.
  16. Jiang, L., Li, J.H. and Li, C.X. (2018), "Comparative study on non-Gaussian characteristics of wind pressure for rigid and flexible structures", Shock Vib., 1-26. https://doi.org/10.1155/2018/9213503.
  17. Jiang, Y., Liu, S., Peng, L. and Zhao, N. (2019), "A novel wind speed prediction method based on robust local mean decomposition, group method of data handling and conditional kernel density estimation", Energy Convers. Manage., 200(15), 112099. https://doi.org/10.1016/j.enconman.2019.112099.
  18. Jiang, Y., Liu, S., Zhao, N., Xin, J. and Wu B. (2020), "Short-term wind speed prediction using time varying filter-based empirical mode decomposition and group method of data handling-based hybrid model", Energy Convers. Manage., 220(15), 113076. https://doi.org/10.1016/j.enconman.2020.113076.
  19. Jiang, Y., Tao, J. and Wang, D. (2014), "Simulation of non-Gaussian stochastic processes by amplitude modulation and phase reconstruction", Wind Struct., 18(6), 693-715. https://doi.org/10.12989/was.2014.18.6.693.
  20. Justin, R.C., Nicholas H.C.L., Andrew F.F. and Gregory S. E. (2012), "Signatures of correlated excitonic dynamics in two-dimensional spectroscopy of the Fenna-Matthew-Olson photosynthetic complex", J. Chemical Phys. 136(10), 104505. https://doi.org/10.1063/1.3690498.
  21. Li, J.H. and Li, C.X. (2012), "Simulation of non-Gaussian stochastic process with target power spectral density and lower-order moments", J. Eng. Mech., 138(5), 391-404. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000349.
  22. Masters, F. and Gurley, K.R. (2003), "Non-Gaussian simulation: Cumulative distribution function map-based spectral correction", J. Eng. Mech., 129(12), 1418-1428. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000349.
  23. Seong, S.H. and Peterka, J.A. (1997), "Computer simulation of non-Gaussian multiple wind press time series", J. Wind Eng. Ind. Aerod., 72(1), 95-105. https://doi.org/10.1016/S0167-6105(97)00243-2.
  24. Seong, S.H. and Peterka, J.A. (1998), "Digital generation of surface-pressure fluctuations with spiky features", J. Wind Eng. Ind. Aerod., 73(2), 181-192. https://doi.org/10.1016/S0167-6105(97)00283-3.
  25. Shinozuka, M. and Jan, C.M. (1972), "Digital simulation of random processes and its applications", J. Sound Vib., 25 (1), 111-128. https://doi.org/10.1016/0022-460X(72)90600-1.
  26. Suresh, K.K. and Stathopoulos, T. (1997), "Computer simulation of fluctuating wind pressures on low building roofs", J. Wind Eng. Ind. Aerod., 69-71(1), 485-495. https://doi.org/10.1016/S0167-6105(97)00179-7.
  27. Suresh, K.K. and Stathopoulos, T. (1999), "Synthesis of non-Gaussian wind pressure time series on low building roofs", Eng. Struct., 21(12), 1086-1100. https://doi.org/10.1016/S0141-0296(98)00069-8.
  28. Tang, J. and Norris, J.R (1986), "LPZ spectral analysis using linear prediction and the z transform", J. Chemical Phys., 84(9), 5210-5211. https://doi.org/10.1063/1.450638.
  29. Tang, J. and Norris, J.R. (1986), "Two-dimensional LPZ spectral analysis with improved resolution and sensitivity", J. Magnetic Resonanc, 69(1), 180-186. https://doi.org/10.1016/0022-2364(86)90234-9.
  30. 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).
  31. Yu, Z., Zhu, F., Cao, R., Chen, X., Zhao, L. and Zhao, S. (2019), "Wind tunnel tests and CFD simulations for snow redistribution on 3D stepped flat roofs", Wind Struct., 28(1), 31-47. https://doi.org/10.12989/was.2019.28.1.031.
  32. Zhang, X.Y., Zhao, Y.G. and Lu, Z.H. (2019), "Unified hermite polynomial model and its application in estimating non-Gaussian processes", J. Eng. Mech., 145(3), 04019001. https://doi.org/10.1061/(ASCE)EM.1943-7889.0001577.
  33. Zhang, Z.H., Liu, Z.H. and Dong, S.L. (2013), "Field measurement of wind pressure and wind-induced vibration of large-span spatial cable-truss system under strong wind or typhoon", J. Shanghai Normal University (Natural Sciences), 42(5), 546-550. (In Chinese).