Error assessment for spectral representation method in wind velocity field simulation

Journal of Engineering Mechanics

Volumn 136, Issue 9, 2010, Pages 1090-1104

  Hu, Liang ^a   Li, Li ^b   Gu, Ming ^a  

^a Tongji University   (China)

^b HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Error assessment; Spectral representation method; Wind field simulation

Indexed keywords

BIAS ERROR; CHOLESKY; CLOSED FORM; CLOSED FORM SOLUTIONS; CORRELATION FUNCTION; ERROR ASSESSMENT; GAUSSIANS; MATHEMATICAL EXPECTATION; MEAN VALUES; NON-GAUSSIAN; NUMERICAL EXAMPLE; SECOND ORDER STATISTICS; SPECTRAL REPRESENTATIONS; STANDARD DEVIATION; STATIONARY GAUSSIAN PROCESS; STOCHASTIC ERRORS; TARGET CHARACTERISTIC; TEMPORAL CORRELATION FUNCTIONS; WIND FIELD SIMULATION; WIND VELOCITY FIELD;

ERRORS; GAUSSIAN DISTRIBUTION; GAUSSIAN NOISE (ELECTRONIC); POWER SPECTRAL DENSITY; SPECTRAL DENSITY; STATISTICS; STOCHASTIC SYSTEMS; VELOCITY;

FLOW VISUALIZATION;

ASSESSMENT METHOD; COMPUTER SIMULATION; CORRELATION; EIGENVALUE; ERROR ANALYSIS; GAUSSIAN METHOD; SPECTRAL ANALYSIS; STOCHASTICITY; TEMPORAL ANALYSIS; WIND VELOCITY;

EID: 81355153876     PISSN: 07339399     EISSN: None     Source Type: Journal    
DOI: 10.1061/(ASCE)EM.1943-7889.0000058     Document Type: Article

References (43)

1. Bendat J.S. Piersol A.G. Random data: Analysis and measurement procedures 1986, and Wiley, New York.
2. Cao Y. Xiang H. Zhou Y. Simulation of stochastic wind velocity field on long-span bridges. J. Eng. Mech. 2000, 126(1):1-6. JENMDT, 0733-9399, 10.1061/(ASCE)0733-9399(2000)126:1(1), and.
3. Carassale L. POD-based filters for the representation of random loads on structures. Probab. Eng. Mech. 2005, 20(3):263-280. PEMEEX, 0266-8920, 10.1016/j.probengmech.2005.05.008.
4. Carassale L. Solari G. Wind modes for structural dynamics: A continuous approach. Probab. Eng. Mech. 2002, 17(2):157-166. PEMEEX, 0266-8920, 10.1016/S0266-8920(01)00036-4, and.
5. Carassale L. Solari G. Monte Carlo simulation of wind velocity fields on complex structures. J. Wind. Eng. Ind. Aerodyn. 2006, 94(5):323-339. JWEAD6, 0167-6105, 10.1016/j.jweia.2006.01.004, and.
6. Carassale L. Solari G. Tubino F. Proper orthogonal decomposition in wind engineering. 2: Theoretical aspects and some applications. Wind Struct. 2007, 10(2):177-208. ZZZZZZ, 1226-6116, and.
7. Chen L. Letchford C.W. Simulation of multivariate stationary Gaussian stochastic processes: Hybrid spectral representation and proper orthogonal decomposition approach. J. Eng. Mech. 2005, 131(8):801-808. JENMDT, 0733-9399, 10.1061/(ASCE)0733-9399(2005)131:8(801), and.
8. Chen X. Kareem A. Proper orthogonal decomposition-based modeling, analysis, and simulation of dynamic wind load effects on structures. J. Eng. Mech. 2005, 131(4):325-339. JENMDT, 0733-9399, 10.1061/(ASCE)0733-9399(2005)131:4(325), and.
9. Chen X. Matsumoto M. Kareem A. Time domain flutter and buffeting response analysis of bridges. J. Eng. Mech. 2000, 126(1):7-16. JENMDT, 0733-9399, 10.1061/(ASCE)0733-9399(2000)126:1(7), and.
10. Deodatis G. Simulation of ergodic multivariate stochastic processes. J. Eng. Mech. 1996, 122(8):778-787. JENMDT, 0733-9399, 10.1061/(ASCE)0733-9399(1996)122:8(778).
11. Ding Q.S. Zhu L.D. Xiang H.F. Simulation of stationary Gaussian stochastic wind velocity field. Wind Struct. 2006, 9(3):231-243. ZZZZZZ, 1226-6116, and.
12. Di Paola M. Digital simulation of wind field velocity. J. Wind. Eng. Ind. Aerodyn. 1998, 74-76:91-109. JWEAD6, 0167-6105, 10.1016/S0167-6105(98)00008-7.
13. Di Paola M. Gullo I. Digital generation of multivariate wind field processes. Probab. Eng. Mech. 2001, 16(1):1-10. PEMEEX, 0266-8920, 10.1016/S0266-8920(99)00032-6, and.
14. Grigoriu M. Errors in simulation of random processes. J. Struct. Eng. 1986, 112(12):2697-2702. JSENDH, 0733-9445, 10.1061/(ASCE)0733-9445(1986)112:12(2697).
15. Grigoriu M. Simulation of stationary process via a sampling theorem. J. Sound Vib. 1993, 166(2):301-313. JSVIAG, 0022-460X, 10.1006/jsvi.1993.1298.
16. Grigoriu M. Algorithm for generating samples of homogeneous Gaussian fields. J. Eng. Mech. 2003, 129(1):43-49. JENMDT, 0733-9399, 10.1061/(ASCE)0733-9399(2003)129:1(43).
17. Hemon P. Santi F. Simulation of a spatially correlated turbulent velocity field using biorthogonal decomposition. J. Wind. Eng. Ind. Aerodyn. 2007, 95(1):21-29. JWEAD6, 0167-6105, 10.1016/j.jweia.2006.04.003, and.
18. Kareem A. Numerical simulation of wind effects: A probabilistic perspective. J. Wind. Eng. Ind. Aerodyn. 2008, 96(10-11):1472-1497. JWEAD6, 0167-6105, 10.1016/j.jweia.2008.02.048.
19. Kitagawa T. Nomura T. A wavelet-based method to generate artificial wind fluctuation data. J. Wind. Eng. Ind. Aerodyn. 2003, 91(7):943-964. JWEAD6, 0167-6105, 10.1016/S0167-6105(03)00037-0, and.
20. Li Y. Kareem A. Simulation of multivariate random processes: Hybrid DFT and digital filtering approach. J. Eng. Mech. 1993, 119(5):1078-1098. JENMDT, 0733-9399, 10.1061/(ASCE)0733-9399(1993)119:5(1078), and.
21. Li Y. Liao H. Qiang S. Simplifying the simulation of stochastic wind velocity fields for long cable-stayed bridges. Comput. Struct. 2004, 82(20-21):1591-1598. CMSTCJ, 0045-7949, 10.1016/j.compstruc.2004.05.007, and.
22. Mignolet M.P. Spanos P.D. Recursive simulation of stationary multivariate random processes-Part I. Trans. ASME, J. Appl. Mech. 1987, 54(3):674-680. JAMCAV, 0021-8936, and.
23. Mignolet M.P. Spanos P.D. Autoregressive spectral modeling. Difficulties and remedies. Int. J. Non-Linear Mech. 1991, 26(6):911-930. IJNMAG, 0020-7462, 10.1016/0020-7462(91)90041-Q, and.
24. Novak D. Stoyanoff S. Herda H. Error assessment for wind histories generated by autoregressive method. Struct. Safety 1995, 17(2):79-90. ZZZZZZ, 0167-4730, 10.1016/0167-4730(95)00003-M, and.
25. Papoulis A. Pillai S.U. Probability, random variables and stochastic processes 2002, and McGraw-Hill, Auckland.
26. Rice S.O. Mathematical analysis of random noise. Selected papers on noise and stochastic processes 1954, 133-294. N. Wax, ed., Dover, New York.
27. Rossi R. Lazzari M. Vitaliani R. Wind field simulation for structural engineering purposes. Int. J. Numer. Methods Eng. 2004, 61(5):738-763. IJNMBH, 0029-5981, 10.1002/nme.1083, and.
28. Shinozuka M. Simulation of multivariate and multidimensional random processes. J. Acoust. Soc. Am. 1971, 49(1B):357-368. JASMAN, 0001-4966, 10.1121/1.1912338.
29. Shinozuka M. Monte Carlo solution of structural dynamics. Comput. Struct. 1972, 2(5-6):855-874. CMSTCJ, 0045-7949, 10.1016/0045-7949(72)90043-0.
30. Shinozuka M. Digital simulation of random processes in engineering mechanics with the aid of FFT technique. Stochastic problems in mechanics 1974, 277-286. S. T. Ariaratnamm, H. H. E. Leipholtz, and eds., University of Waterloo Press, Waterloo, Canada.
31. Shinozuka M. Stochastic fields and their digital simulation. Stochastic methods in structural dynamics 1987, 93-133. G. I. Schuller, M. Shinozuka, and eds., Martinus Nijhoff, Dordrecht, The Netherlands.
32. Shinozuka M. Deodatis G. Simulation of stochastic processes by spectral representation. Appl. Mech. Rev. 1991, 44(4):191-204. AMREAD, 0003-6900, 10.1115/1.3119501, and.
33. Shinozuka M. Deodatis G. Simulation of multi-dimensional Gaussian stochastic fields by spectral representation. Appl. Mech. Rev. 1996, 49(1):29-53. AMREAD, 0003-6900, 10.1115/1.3101883, and.
34. Shinozuka M. Jan C.M. Digital simulation of random processes and its applications. J. Sound Vib. 1972, 25(1):111-128. JSVIAG, 0022-460X, 10.1016/0022-460X(72)90600-1, and.
35. Shinozuka M. Yun C.B. Seya H. Stochastic methods in wind engineering. J. Wind. Eng. Ind. Aerodyn. 1990, 36(1-3):829-843. JWEAD6, 0167-6105, 10.1016/0167-6105(90)90080-V, and.
36. Solari G. Carassale L. Modal transformation tools in structural dynamics and wind engineering. Wind Struct. 2000, 3(4):221-241. ZZZZZZ, 1226-6116, and.
37. Solari G. Carassale L. Tubino F. Proper orthogonal decomposition in wind engineering. 1: A state-of-the-art and some prospects. Wind Struct. 2007, 10(2):153-176. ZZZZZZ, 1226-6116, and.
38. Solari G. Tubino F. A turbulence model based on principal components. Probab. Eng. Mech. 2002, 17(4):327-335. PEMEEX, 0266-8920, 10.1016/S0266-8920(02)00016-4, and.
39. Suresh Kumar K. Random number sensitivity in simulation of wind loads. Wind Struct. 2000, 3(1):1-10. ZZZZZZ, 1226-6116.
40. Tubino F. Solari G. Double proper orthogonal decomposition for representing and simulating turbulence fields. J. Eng. Mech. 2005, 131(12):1302-1312. JENMDT, 0733-9399, 10.1061/(ASCE)0733-9399(2005)131:12(1302), and.
41. Yang J.N. Simulation of random envelope processes. J. Sound Vib. 1972, 21(1):73-85. JSVIAG, 0022-460X, 10.1016/0022-460X(72)90207-6.
42. Yang W.W. Chang T.Y. P. Numerical simulation of turbulent fluctuations along the axis of a bridge. Eng. Struct. 1998, 20(9):837-848. ENSTDF, 0141-0296, 10.1016/S0141-0296(97)00112-0, and.
43. Yang W.W. Chang T.Y. P. Chang C.C. An efficient wind-field simulation technique for bridges. J. Wind. Eng. Ind. Aerodyn. 1997, 67-68:697-708. JWEAD6, 0167-6105, 10.1016/S0167-6105(97)00111-6, and.