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Approximation of crossing intensities for non linear responses subjected to non Gaussian loadings

Thomas Galtier (Institutionen för matematiska vetenskaper) ; S. Gupta ; Igor Rychlik (Institutionen för matematiska vetenskaper, matematisk statistik)
Proceedings of the ASME 29th International Conference on Ocean, Offshore and Arctic Engineering (OMAE 2010) in Shanghai, China, June 6-11, 2010 Vol. 2 (2010), p. 109-121.
[Konferensbidrag, refereegranskat]

Crossing intensity constitute an important response characteristic for randomly vibrating structures, especially if one is interested in estimating the risk against failures. This paper focusses on developing approximations by which estimates of the crossing intensities for response of marine structures can be obtained in a computationally efficient manner, when the loads are modeled as a special class of non-Gaussian processes, namely as LMA processes. Ocean waves exhibit considerable non-Gaussianity as marked by their skewed marginal distributions and heavy tails. Here, a new class of processes the Laplace driven Moving Average (LMA) processes are used to model the ocean waves. LMA processes are non-Gaussian, strictly stationary, can model in principle any spectrum and have the additional flexibility to model the skewness and the kurtosis of the marginal distribution. The structure behavior assumed is limited to quadratic systems characterized by second order kernels, which is common for marine structures. Thus, an estimation of the crossing intensities of the response involves studying the crossing characteristics of a LMA process passing through a second order filter. A new computationally efficient hybrid method, which uses the saddle point approximations along with limited Monte Carlo simulations, is developed to compute crossing intensity of the response. The proposed method is illustrated through numerical examples.

Denna post skapades 2011-11-22.
CPL Pubid: 148850


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Institutioner (Chalmers)

Institutionen för matematiska vetenskaperInstitutionen för matematiska vetenskaper (GU)
Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)


Tillämpad matematik

Chalmers infrastruktur