Technical Notes
Dec 14, 2011

Error Assessment for Spectral Representation Method in Random Field Simulation

Publication: Journal of Engineering Mechanics
Volume 138, Issue 6

Abstract

Random fields, such as the wind velocity field and the seismic ground motion field, are usually simulated by the spectral representation method (SRM). The SRM mainly relies on two methods: the random amplitudes method and the random phases method. However, the temporal statistics estimated from one SRM-simulated sample process differs from the target characteristics. Such differences can usually be assessed by the statistical errors, i. e., bias errors and stochastic errors. The closed-form solutions of statistical errors produced by random phases method have been given. This paper gives the closed-form solutions of statistical errors produced by the random phases methods and compares the statistical errors produced by both methods. The comparison of the stochastic errors of power spectral density functions produced by different methods demonstrates that (1) the random amplitudes method exhibits higher but more uniformly distributed stochastic errors than the random phases method; and (2) the stochastic errors produced by the random phases method are dependent on the decomposition method, whereas those produced by the random amplitudes method are not.

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Acknowledgments

This research was supported by the National Natural Science Foundation of China (Grants 90815020, 50825901, and 50808067).

References

Bendat, J. S., and Piersol, A. G. (1986). Random data: Analysis and measurement procedures, Wiley, New York.
Carassale, L., and Solari, G. (2002). “Wind modes for structural dynamics: A continuous approach.” Prob. Eng. Mech.PEMEEX, 17(2), 157–166.
Carassale, L., and Solari, G. (2006). “Monte Carlo simulation of wind velocity fields on complex structures.” J. Wind Eng. Ind. Aerodyn., 94(5), 323–339.JWEAD6
Chen, L., and Letchford, C. W. (2005). “Simulation of multivariate stationary Gaussian stochastic processes: Hybrid spectral representation and proper orthogonal decomposition approach.” J. Eng. Mech.JENMDT, 131(8), 801–808.
Chen, X., and Kareem, A. (2005). “Proper orthogonal decomposition-based modeling, analysis, and simulation of dynamics wind load effects on structures.” J. Eng. Mech.JENMDT, 131(4), 325–339.
Deodatis, G. (1996a). “Simulation of ergodic multivariate stochastic processes.” J. Eng. Mech.JENMDT, 122(8), 778–787.
Deodatis, G. (1996b). “Non-stationary stochastic vector processes: seismic ground motion applications.” Prob. Eng. Mech.PEMEEX, 11(3), 149–168.
Di Paola, M. (1998). “Digital simulation of wind field velocity.” J. Wind Eng. Ind. Aerodyn., 74–76(1), 91–109.JWEAD6
Di Paola, M., and Gullo, I. (2001). “Digital generation of multivariate wind field processes.” Prob. Eng. Mech.PEMEEX, 16(1), 1–10.
Di Paola, M., and Pisano, A. A. (1996). “Multivariate stochastic wave generation.” Appl. Ocean Res., 18(6), 361–365.AOCRDS
Di Paola, M., and Zingales, M. (2000). “Digital simulation of multivariate earthquake ground motions.” Earthquake Eng. Struct. Dyn.IJEEBG, 29(7), 1011–1027.
Hao, H., Oliveira, C. S., and Penzien, J. (1989). “Multiple-station ground motion processing and simulation based on SMART-1 array date.” Nucl. Eng. Des., 111(3), 293–310.NEDEAU
Harichandran, R. S., and Vanmarcke, E. H. (1986). “Stochastic variation of earthquake ground motion in space and time.” J. Eng. Mech.JENMDT, 112(2), 154–174.
Hu, L., Li, L., and Gu, M. (2010). “Error assessment for spectral representation method in wind velocity field simulation.” J. Eng. Mech.JENMDT, 136(9), 1090–1104.
Rice, S. O. (1954). “Mathematical analysis of random noise.” Selected papers on noise and stochastic processes, Wax, N., ed. Dover, New York, 133–294.
Shinozuka, M. (1971). “Simulation of multivariate and multidimensional random processes.” J. Acoust. Soc. Am.JASMAN, 49(1B), 357–368.
Shinozuka, M. (1972). “Monte-Carlo solution of structural dynamics.” Comput. Struct.CMSTCJ, 2(5–6), 855–874.
Shinozuka, M., and Deodatis, G. (1991). “Simulation of stochastic processes by spectral representation.” Appl. Mech. Rev., 44(4), 191–204.AMREAD
Shinozuka, M., and Deodatis, G. (1996). “Simulation of multi-dimensional Gaussian stochastic fields by spectral representation.” Appl. Mech. Rev., 49(1), 29–53.AMREAD
Shinozuka, M., and Jan, C. M. (1972). “Digital simulation of random processes and its application.” J. Sound Vib.JSVIAG, 25(1), 111–128.
Shinozuka, M., Yun, C. B., and Seya, H. (1990). “Stochastic methods in wind engineering.” J. Wind Eng. Ind. Aerodyn.JWEAD6, 36(2), 829–843.
Yang, J. N. (1972). “Simulation of random envelope processes.” J. Sound Vib.JSVIAG, 21(1), 73–85.

Information & Authors

Information

Published In

Go to Journal of Engineering Mechanics
Journal of Engineering Mechanics
Volume 138Issue 6June 2012
Pages: 711 - 715

History

Received: Jan 21, 2011
Accepted: Dec 12, 2011
Published online: Dec 14, 2011
Published in print: Jun 1, 2012

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Authors

Affiliations

Professor, Research Institute of Geotechnical Engineering, Hohai Univ., Xikang Rd. 1, Nanjing 210098, China (corresponding author). E-mail: [email protected]
Yongxin Wu
Ph.D. Candidate, Research Institute of Geotechnical Engineering, Hohai Univ., Xikang Rd. 1, Nanjing 210098, China.
Yuanqiang Cai
Professor, College of Architecture and Civil Engineering, Wenzhou Univ., Chashan Univ. Town, Wenzhou 325035, China.
Hanlong Liu
Professor, Research Institute of Geotechnical Engineering, Hohai Univ., Xikang Rd. 1, Nanjing 210098, China.
Dayong Li
Professor, College of Civil Engineering, Shandong Univ. of Science and Technology, Qingdao 266590, China.
Ning Zhang
Ph.D. Candidate, Research Institute of Geotechnical Engineering, Hohai Univ., Xikang Rd. 1, Nanjing 210098, China.

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