Browse > Article
http://dx.doi.org/10.12989/was.2021.33.1.055

Fast simulation of large-scale non-stationary wind velocities based on adaptive interpolation reconstruction scheme  

Han, Hui (Department of Civil Engineering, School of Mechanics and Engineering Science, Shanghai University)
Li, Chunxiang (Department of Civil Engineering, School of Mechanics and Engineering Science, Shanghai University)
Li, Jinhua (Department of Civil Engineering, East China Jiaotong University)
Publication Information
Wind and Structures / v.33, no.1, 2021 , pp. 55-69 More about this Journal
Abstract
Spectral representation method (SRM) is the most classical one for the simulation of wind velocity. It is inefficiency when applied to large-scale non-stationary wind velocities with large simulation points. There are two reasons: numerous Cholesky decomposition and summation of Trigonometric terms. In order to improve the efficiency while ensuring accuracy, two aspects of work have been in this paper. (1) An adaptive interpolation-enhanced scheme is devised, which uses "average resolution" as the quantization index. This scheme can automatically realize the non-uniform distribution of interpolation points in two dimensions of time and frequency simultaneously, and improve the accuracy of interpolation. (2) The non-stationary wind velocities were reconstructed in time, frequency and space domain. Firstly, interpolation in time and frequency domain is directly applied to the H matrix, then proper orthogonal decomposition (POD) technology is introduced to decouple the wind velocities at spatial interpolation points, so as to obtain the time-dependent principal coordinates and space-dependent intrinsic mode function (IMF). Finally, IMF is reconstructed in the space domain to obtain the complete wind velocities. The above methodology is carried out to a super high-rise building containing 100 wind velocities simulation points and, results show that the proposed approach saves about 88% of the computational time compared with the classical SRM; saves about 47% of the computational time compared with the time-frequency interpolation based method. This paper achieves the rapid construction of large-scale non-stationary wind velocities.
Keywords
non-stationary; spectral representation method; proper orthogonal decomposition; Cholesky decomposition; time-frequency-space reconstruction; adaptive scheme;
Citations & Related Records
Times Cited By KSCI : 4  (Citation Analysis)
연도 인용수 순위
1 Rice, S.O. (1944), "Mathematical analysis of random noise", Bell Syst. Tech., 23(3), 282-332. https://doi.org/10.1002/j.1538-7305.1944.tb00874.x.   DOI
2 Shinozuka, M. and Deodatis, G. (1991), "Simulation of stochastic processes by spectral representation", Appl. Mech. Rev., 44(4), 191-204. https://doi.org/10.1115/1.3119501.   DOI
3 Shinozuka, M. and Jan, C.M. (1972), "Digital simulation of random processes and its applications", Sound Vib., 25(1), 111-128. https://doi.org/10.1016/0022-460x(72)90600-1.   DOI
4 Grigoriu, M. (1993), "On the spectral representation method in simulation", Probabilistic Eng. Mech., 8(2), 75-90. https://doi.org/10.1016/0266-8920(93)90002-d.   DOI
5 Gurley, K. and Kareem, A. (1997), "Analysis interpretation modeling and simulation of unsteady wind and pressure data", Wind Eng. Ind. Aerod., 69-71(Jul-Oc), 657-669. https://doi.org/10.1016/S0167-6105(97)00195-5.   DOI
6 Gurley, K., Kareem, A. and Tognarelli, M.A. (1996), "Simulation of a class of non-normal random processes", Non Linear Mech., 31(5), 601-617. https://doi.org/10.1016/0020-7462(96)00025-X.   DOI
7 Huang, G.Q. (2015), "Application of proper orthogonal decomposition in fast fourier transform-assisted multivariate nonstationary process simulation", Eng. Mech., 141(7), 04015015. https://doi.org/10.1061/(ASCE)EM.1943-7889.0000923.   DOI
8 Song, Y.P., Chen, J.B., Peng, Y.B., Spanos, P.D. and Li, J. (2018), "Simulation of nonhomogeneous fluctuating wind speed field in two-spatial dimensions via an evolutionary wavenumberfrequency joint power spectrum", Wind Eng. Ind. Aerod., 179, 250-259. https://doi.org/10.1016/j.jweia.2018.06.005.   DOI
9 Spanos, P.D. and Mignolet, M.P. (1989) "ARMA Monte Carlo simulation in probabilistic structural analysis", Shock Vib., 21(11), 3-14. https://doi.org/10.1177/058310248902101103.   DOI
10 Wang, H., Xu, Z.D., Wu, T. and Mao, J.X. (2018), "Evolutionary power spectral density of recorded typhoons at Sutong Bridge using harmonic wavelets", Wind Eng. Ind. Aerod., 177, 197-212. http://doi.org/10.1016/j.jweia.2018.04.015.   DOI
11 Wang, H.F. and Wu, T. (2020), "Time-varying multiscale spatial correlation: Simulation and application to wind loading of structures", Struct. Eng-ASCE, 146(7), 04020138. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002689.   DOI
12 Yamazaki, F. and Shinozuka, M. (1988), "Digital generation of non-Gaussian stochastic fields", Eng. Mech., 114(7), 1183-1197. https://doi.org/10.1061/(ASCE)0733-9399(1988)114:7(1183).   DOI
13 Hui, Y., Li, B., Kawai, H. and Yang, Q.S. (2017), "Non-stationary and non-Gaussian characteristics of wind speeds", Wind Struct., 24(1), 59-78. http://dx.doi.org/10.12989/was.2017.24.1.059.   DOI
14 Yang, J.N. (1972), "Simulation of random envelope process", Sound Vib., 21(1), 73-85. https://doi.org/10.1016/0022-460X(72)90207-6.   DOI
15 Yu, C.J., Li, Y.L., Zhang, M.J., Zhang, Y. and Zhai, G.H. (2019), "Wind characteristics along a bridge catwalk in a deep-cutting gorge from field measurements", Wind Eng. Ind. Aerod., 186, 94-104. https://doi.org/10.1016/j.jweia.2018.12.022.   DOI
16 Huang, Z.F. and Gu, M. (2019), "Characterizing nonstationary wind speed using the AR-MA-GARCH model", Struct. Eng., 145(1), 04018226. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002211.   DOI
17 Huang, G.Q., Liao, H.L. and Li, M.S. (2013), "New formulation of Cholesky decomposition and applicationsin stochastic simulation", Probabilist. Eng. Mech., 34, 40-47. https://doi.org/10.1016/j.probengmech.2013.04.003.   DOI
18 Jiang, Y., Zhao, N., Peng, L.L., Zhao, L.N. and Liu, M. (2019), "Simulation of stationary wind field based on adaptive interpolation-enhanced scheme", Wind Eng. Ind. Aerod., 195, 104001. https://doi.org/10.1016/j.jweia.2019.104001.   DOI
19 Yuan, Q.L. and Tamura, Y. (2005), "Equivalent static wind load estimation in wind-resistant design of single-layer reticulated shells", Wind Struct., 8(6), 443-454. http://dx.doi.org/10.12989/was.2005.8.6.443.   DOI
20 Zhao, N. and Huang, G.Q. (2020), "Wind velocity field simulation based on enhanced closed-form solution of Cholesky dcomposition", Eng. Mech., 146(2), 04019128. https://doi.org/10.1061/(ASCE)EM.1943-7889.0001712.   DOI
21 Kaimal, J.C., Wyngaard, J.C., Izumi, Y. and Cote, O.R. (1972), "Spectral characteristics of surface-layer turbulence", Meteor. Soc., 98(417), 563-589. https://doi.org/10.1002/qj.49709841707.   DOI
22 Li, C.X. and Du, M. (2008), "Simulation of fluctuating wind velocity time series around super-tall buildings", Vib. Shock, 27(3), 124-130. https://doi.org/10.13465/j.cnki.jvs.2008.03.030.   DOI
23 Li, F.H., Ni, Z.H., Shen, S.Z. and Gu, M. (2009), "POD Theory of POD and its application in wind engineering of structures", Vib. Shock, 28(4), 29-32+201. https://doi.org/10.3969/j.issn.1000-3835.2009.04.007.   DOI
24 Li, Y.S. and Kareem, A. (1995), "Stochastic decomposition and application to probabilistic dynamics", Eng. Mech., 121(1), 162-174. https://doi.org/10.1061/(ASCE)0733-9399(1995)121:1(162).   DOI
25 Priestley, M.B. (1967), "Power spectral analysis of non-stationary random processes", Sound Vib., 6(1), 86-97. https://doi.org/10.1016/0022-460X(67)90160-5.   DOI
26 Liang, J.W., Chaudhuri, S.R. and Shinozuka, M. (2007), "Simulation of nonstationary stochastic processes by spectral representation", Eng. Mech., 133(6), 616-627. https://doi.org/10.1061/(ASCE)0733-9399(2007)133:6(616).   DOI
27 Mignolet, M.P. and Spanos, P.D. (1990), "MA to ARMA modeling of wind", Wind Eng. Ind. Aerod., 36(1-3), 429-438. https://doi.org/10.1016/0167-6105(90)90326-8.   DOI
28 Priestley, M.B. (1965), "Evolutionary spectra and non-stationary processes", Roy. Stat. Soc., 27(2), 204-237. https://doi.org/10.1111/j.2517-6161.1965.tb01488.x.   DOI
29 Li, J.H., Li, C.X., He, L. and Shen, J.H. (2015), "Extended modulating functions for simulation of wind velocities with weak and strong nonstationarity", Renew. Energy, 83, 384-397. https://doi.org/10.1016/j.renene.2015.04.044.   DOI
30 Aly, A.M. and Hamzeh, G.Z. (2020), "Peak pressures on low rise buildings: CFD with LES versus full scale and wind tunnel measurements", Wind Struct., 30(1), 99-117. http://dx.doi.org/10.12989/was.2020.30.1.099.   DOI
31 Bai, Z.Z., Miao, C.Q. and Jian, S. (2019), "On multistep Rayleigh quotient iterations for Hermitian eigenvalue problems", Comput. Math. Appl., 77(9), 2396-2406. https://doi.org/10.1016/j.camwa.2018.12.025.   DOI
32 Chan, K.T., Stephen, N.G. and Young, K. (2011), "Perturbation theory and the Rayleigh quotient", J. Sound Vib., 330(9), 2073-2078. https://doi.org/10.1016/j.jsv.2010.11.001.   DOI
33 Tao, T.Y., Wang, H. and Zhao, K.Y. (2021), "Efficient simulation of fully non-stationary random wind field based on reduced 2D hermite interpolation", Mech. Syst. Signal Pr., 150, 107265.   DOI
34 Von Karman, T. (1948), "Progress in the statistical theory of turbulence", Proc. Natl. Acad. Sci. U.S.A., 34(11), 530-539. https://doi.org/10.2307/88224.   DOI
35 Xie, Z.N., Ni, Z.H. and Shi, B.Q. (2001), "Experimental Investigation on Characteristics of Wind Load on Large Span Roof", Build. Struct., 22(2), 23-28. https://doi.org/10.3321/j.issn:1000-6869.2001.02.004.   DOI
36 Yang, J.N. (1973), "On the normality and accuracy of simulated random processes", Sound Vib., 26(3), 417-428. https://doi.org/10.1016/s0022-460x(73)80196-8.   DOI
37 Zhang, M.J., Zhang, J.X., Li, Y.L., Yu, J.S., Zhang, J.Y. and Wu, L.H. (2020), "Wind characteristics in the high-altitude difference at bridge site by wind tunnel tests", Wind Struct., 30(6), 547-558. http://dx.doi.org/10.12989/was.2020.30.6.547.   DOI
38 Feng, R.Q., Liu, F.C., Cai, Q., Yan, G.R. and Leng, J.B. (2018), "Field measurements of wind pressure on an open roof during Typhoons HaiKui and SuLi", Wind Struct., 26(1), 11-14. http://dx.doi.org/10.12989/was.2018.26.1.011.   DOI
39 Huang, G.Q., Peng, L.L., Kareem, A. and Song, C.C. (2020), "Data-driven simulation of multivariate nonstationary winds: A hybrid multivariate empirical mode decomposition and spectral representation method", Wind Eng. Ind. Aerod., 197, 104073. https://doi.org/10.1016/j.jweia.2019.104073.   DOI
40 Tao, T.Y., Wang, H., Yao, C.Y., He, X.H. and Kareem, A. (2018), "Efficacy of interpolation enhanced schemes in random wind field simulation over long-span bridges", Bridge Eng., 23(3), 04017147. https://doi.org/10.1061/(ASCE)BE.1943-5592.0001203.   DOI
41 Tao, T.Y., Wang, H., Hu, L. and Kareem, A. (2020), "Error Analysis of Multivariate Wind Field Simulated by Interpolationenhanced spectral representation method", Eng. Mech., 146(6), 04020049. https://doi.org/10.1061/(ASCE)EM.1943-7889.0001783.   DOI
42 Bao, X.M. and Li, C.X. (2019), "Fast simulation of non-stationary wind velocity based on time-frequency interpolation", Wind Eng. Ind. Aerod, 193, 103982. https://doi.org/10.1016/j.jweia.2019.103982.   DOI
43 Deng, T., Fu, J.Y., Zheng, Q.X. and Wu, J.R. (2019), "Performance-based wind-resistant optimization design for tall building structures", Struct. Eng., 145(10), 04019103. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002383.   DOI
44 Deodatis, G. (1996), "Simulation of ergodic multivariate stochastic processes", Eng. Mech., 122(8), 778-787. https://doi.org/10.1061/(ASCE)0733-9399(1996)122:8(778).   DOI
45 Ding, Q.S., Zhu, L.D. and Xiang, H.F. (2006), "Simulation of stationary Gaussian stochastic wind velocity field", Wind Struct., 3(9), 231-243. http://dx.doi.org/10.12989/was.2006.9.3.231.   DOI
46 Deodatis, G. and Shinozuka, M. (1988), "Autoregressive model for nonstationary stochastic processes", Eng. Mech., 114(11), 1995-2012. https://doi.org/10.1061/(ASCE)0733-9399(1988)114:11(1995).   DOI
47 Di Paola, M. (1998), "Digital simulation of wind field velocity", Wind Eng. Ind. Aerod., 74-76(2), 91-109. https://doi.org/10.1016/S0167-6105(98)00008-7.   DOI
48 Di Paola, M., Muscolino, G. and Sofi, A. (2004), "Monte Carlo simulation for the response analysis of long-span suspended cables under wind loads", Wind Struct., 7(2), 107-130. http://dx.doi.org/10.12989/was.2004.7.2.107.   DOI
49 Fiore, A. and Monaco, P. (2009), "POD-based representation of the alongwind Equivalent Static Force for long-span bridges", Wind Struct., 12(3), 239-257. http://dx.doi.org/10.12989/was.2009.12.3.239.   DOI
50 Franke, R. (1982), "Scattered data interpolation: test of some methods", Comput. Math., 33(157), 181-200. https://doi.org/10.1090/S0025-5718-1982-0637296-4.   DOI
51 Li, Z.H. and Wang, H.H. (2010), "Comparison of gravimetric data meshing methods", Geod. Geodyn., 30(1), 140-144. https://doi.org/10.14075/j.jgg.2010.01.019.   DOI
52 Davenport, A.G. (1960), "The spectrum of horizontal gustiness near the ground in high winds", Meteor. Soc., 87(372), 194-211. https://doi.org/10.1002/qj.49708737208.   DOI