Z‐Transform Modeling of P‐M Wave Spectrum
Publication: Journal of Engineering Mechanics
Volume 112, Issue 8
Abstract
The approximation of the Pierson‐Moskowitz (P‐M) wave spectrum as the output of digital filters to white noise excitation is considered. It is shown that the mathematical peculiarity of this spectrum is the source of the numerical difficulties encountered in approximating it by autoregressive (AR) models. Further, it is shown that a reasonably accurate initial AR approximation leads to quite efficient autoregressive moving average (ARMA) models. This is accomplished by employing two new techniques. Numerical data are given in a dimensionless form so that they are applicable to a variety of structural dynamics applications.
Get full access to this article
View all available purchase options and get full access to this article.
References
1.
Cheney, E. W., Introduction to Approximation Theory, McGraw Hill, New York, N.Y., 1966.
2.
Gersch, W., and Yonemoto, J., “Synthesis of Multivariate Random Vibration Systems: A Two‐Stage Least Squares AR‐MA Model Approach,” Journal of Sound and Vibration, Vol. 52, No. 4, 1977, pp. 553–565.
3.
Graupe, D., Krause, D. J., Moore, J. B., “Identification of Autoregressive Moving‐Average Parameters of Time Series,” IEEE Transactions in Automatic Control, Vol. AC‐20, Feb., 1975, pp. 104–107.
4.
Grenander, U., and Szegö, G., Toeplitz Forms and Their Applications, University of California Press, Berkeley, Calif., 1958.
5.
Hudspeth, R. T., and Borgman, L. E., “Efficient FFT Simulation of Digital Time Sequences,” Journal of the Engineering Mechanics Division, ASCE, Vol. 105, No. EM2, Apr., 1979, pp. 223–235.
6.
Koopmans, L. H., The Spectral Analysis of Time Series, Academic Press, New York, N.Y., 1974.
7.
Pierson, W. J., and Moskowitz, L., “A Proposed Spectral Form for Fully Developed Wind Seas Based on the Similarity Theory of S. A. Kitaigorodskii,” Journal of Geophysical Research, Vol. 69, No. 24, 1964, pp. 5181–5190.
8.
Rozanov, Y. A., Stationary Random Processes, Holden Day, San Francisco, Calif., 1967.
9.
Samaras, E. F., Shinozuka, M., and Tsurui, A., “ARMA Representation of Random Vector Processes,” Journal of Engineering Mechanics, ASCE, Vol. 111, No. 3, Mar., 1985, pp. 449–461.
10.
Samii, K., and Vandiver, J. K., “A Numerically Efficient Technique for the Simulation of Random Wave Forces on Offshore Structures,” Proceedings, of the Sixteenth Annual Ocean Technology Conference in Houston, Tex., OTC 4811, May, 1984, pp. 301–305.
11.
Shinozuka, M., “Monte Carlo Solution of Structural Dynamics,” Computers and Structures, Vol. 2, 1972, pp. 855–874.
12.
Shinozuka, M., and Wai, P., “Digital Simulation of Short‐Crested Sea Surface Elevations,” Journal of Ship Research, Vol. 23, No. 1, Mar., 1979, pp. 76–84.
13.
Spanos, P.‐T. D., and Hansen, J. E., “Linear Prediction Theory for Digital Simulation of Sea Waves,” Journal of Energy Resources Technology, ASME, Vol. 103, Sept., 1981, pp. 243–249.
14.
Spanos, P.‐T. D., “ARMA Algorithms for Ocean Wave Modeling,” Journal of Energy Resources Technology, ASME, Vol. 105, Sept., 1983, pp. 300–309.
15.
Spanos, P.‐T. D., and Schultz, K. P., “Two‐Stage Order‐of‐Magnitude Matching for the von Karman Turbulence Spectrum,” Proceedings of the Fourth International Conference on Structural Safety and Reliability, ICOSSAR, Vol. 1, 1985, pp. 211–218.
16.
Spanos, P.‐T. D., and Schultz, K. P., “Numerical Synthesis of Tri‐Variate Velocity Realizations of Turbulence,” International Journal of Non‐Linear Mechanics, 1986, to be published.
17.
Varga, R. S., Matrix Iterative Analysis, Prentice Hall, Englewood Cliffs, N.J., 1962.
Information & Authors
Information
Published In
Copyright
Copyright © 1986 ASCE.
History
Published online: Aug 1, 1986
Published in print: Aug 1986
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.