Digital Generation of Non-Gaussian Spiky Excitations Using Spectral Representation with Additive Phase Structure
Publication: Journal of Engineering Mechanics
Volume 138, Issue 10
Abstract
This paper presents a framework of the digital generation of non-Gaussian spiky excitations. This study is focused on the random spikiness, featuring large excursions with considerable energy and monotonic (nonstochastic) variations in a local time history. A first-order non-Gaussian stochastic time series model and its spectral representation are employed for the local spiky features. The stochastic model generates not only autocorrelation properties but also a unique shape of peaks formed with random spikes and monotonic variations between spikes. The Fourier representation of the stochastic model enables an effective control of the peaks and provides a filtering operation for the local feature generation in the frame of stationary stochastic process. Several spectral models with stochastic or ensemble-averaged amplitudes and four added phase functions have been developed. Thus, the phase is different from the uncorrelated uniform phases in a conventional spectral method. The essential feature of the method is to utilize correlations in the structured phase that are responsible for the spikiness. A four-parameter system is developed that is capable of generating spiky features while simulating specified power spectra and higher-order moments. A simple procedure for the selection of phase parameter values by a graphical method is described with illustrations of surface pressure simulation.
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Acknowledgments
The first author thanks Dr. B. Bienkiewicz for the visiting research opportunity and Professor V. Sandborn for proofreading and valuable comments.
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Information
Published In
Journal of Engineering Mechanics
Volume 138 • Issue 10 • October 2012
Pages: 1236 - 1248
Copyright
© 2012 American Society of Civil Engineers.
History
Received: Nov 20, 2010
Accepted: Feb 29, 2012
Published online: Mar 3, 2012
Published in print: Oct 1, 2012
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