[en] Based on the observation of the existence of different timescales, this paper provides an approximate method to compute the kurtosis coefficient of the response of a linear-time-invariant system subjected to a low-frequency non Gaussian input. While the kurtosis coefficient is formally obtained by a multidimensional integration of the corresponding spectrum, the proposed method only requires the estimation of a single definite integral. The speedup performance is three to four orders of magnitude and the approximation is very accurate as it corresponds to the leading order expansion of the formal solution, with the ratio of the identified timescales considered as a small parameter.
Disciplines :
Civil engineering
Author, co-author :
Denoël, Vincent ; Université de Liège - ULiège > Département ArGEnCo > Analyse sous actions aléatoires en génie civil
Language :
English
Title :
Extension of the Background/biResonant decomposition to the estimation of the kurtosis coefficient of the response
Publication date :
September 2012
Event name :
Uncertainty in Structural Dynamics
Event place :
Leuven, Belgium
Event date :
17-19 September 2012
Audience :
International
Main work title :
Proceedings of the Conference on Uncertainty in Structural Dynamics
Ashraf Ali, M. and P.L. Gould, On the resonant component of the response of single degree-of-freedom systems under random loading. Engineering Structures, 1985. 7(4): p. 280-282.
Benfratello, S. and G. Falsone, Non-Gaussian Approach For Stochastic-Analysis Of Offshore Structures. Journal Of Engineering Mechanics-Asce, 1995. 121(11): p. 1173-1180.
Benfratello, S., M. Di Paola, and P.D. Spanos, Stochastic response of MDOF wind-excited structures by means of Volterra series approach. Journal Of Wind Engineering And Industrial Aerodynamics, 1998. 74-6: p. 1135-1145.
Carassale, L. and A. Kareem, Dynamic analysis of complex systems by Volterra approach. Computational Stochastic Mechanics, 2003: p. 107-117.
Carassale, L. and A. Kareem, Modeling nonlinear systems by Volterra Series. Journal of Engineering Mechanics ASCE, 2010. 136: p. 801-818.
Davenport, A.G., The application of statistical concepts to the wind loading of structures. Proceedings of the Institute of Civil Engineers, 1961. 19: p. 449-472.
Denoël, V., Application of stochastic analysis methods to the study of the effects of wind on civil engineering structures, PhD thesis, Department of Mechanics and Structures 2005, University of Liège: Liège.
Denoël, V., On the background and biresonant components of the random response of single degreeof- freedom systems under non-Gaussian random loading. Engineering Structures, 2011. 33(8): p. 2271-2283.
Gusella, V. and A.L. Materazzi, Non-Gaussian response of MDOF wind-exposed structures: Analysis by bicorrelation function and bispectrum. Meccanica, 1998. 33(3): p. 299-307.
Kareem, A., J. Zhao, and M.A. Tognarelli, Surge response statistics of tension leg platforms under wind and wave loads: A statistical quadratization approach. Probabilistic Engineering Mechanics, 1995. 10(4): p. 225-240.
Schetzen M., The Volterra and Wiener Theories of Nonlinear Systems 1980.
Solari, G. and G. Piccardo, Probabilistic 3-D turbulence modeling for gust buffeting of structures. Probabilistic Engineering Mechanics, 2001. 16(1): p. 73-86.
Worden, K. and G. Manson, Random vibrations of a Duffing oscillator using the Volterra series. Journal Of Sound And Vibration, 1998. 217(4): p. 781-789
Similar publications
Sorry the service is unavailable at the moment. Please try again later.
This website uses cookies to improve user experience. Read more
Save & Close
Accept all
Decline all
Show detailsHide details
Cookie declaration
About cookies
Strictly necessary
Performance
Strictly necessary cookies allow core website functionality such as user login and account management. The website cannot be used properly without strictly necessary cookies.
This cookie is used by Cookie-Script.com service to remember visitor cookie consent preferences. It is necessary for Cookie-Script.com cookie banner to work properly.
Performance cookies are used to see how visitors use the website, eg. analytics cookies. Those cookies cannot be used to directly identify a certain visitor.
Used to store the attribution information, the referrer initially used to visit the website
Cookies are small text files that are placed on your computer by websites that you visit. Websites use cookies to help users navigate efficiently and perform certain functions. Cookies that are required for the website to operate properly are allowed to be set without your permission. All other cookies need to be approved before they can be set in the browser.
You can change your consent to cookie usage at any time on our Privacy Policy page.