| Titre : | Digital generation of non-gaussian spiky excitations using spectral representation with additive phase structure (2012) |
| Auteurs : | Seung H. Seong, Auteur ; Jon A. Peterka, Auteur |
| Type de document : | Article : texte imprimé |
| Dans : | Journal of engineering mechanics (Vol. 138 N° 10, Octobre 2012) |
| Article en page(s) : | pp. 1236–1248. |
| Note générale : | Mécanique appliquée |
| Langues : | Anglais |
| Tags : | Digital random data generation Non-Gaussian distribution Spectral method Phase structure |
| Résumé : | 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. |
| ISSN : | 0733-9399 |
| En ligne : | http://ascelibrary.org/doi/abs/10.1061/%28ASCE%29EM.1943-7889.0000431 |
