Deck slamming phenomenon is one of the most critical factors in the design of column-stabilizing platforms. However, the prediction of its occurrence is not simple due to nonlinear effects in wave elevation and platform motion. In this paper, a stochastic approach is proposed to predict efficiently the probability of deck-slamming occurence for offshore structures. The present approach is based on the assumption of potential flow up to the second order and has four steps: representing relative wave elevation as two-term Volterra series, solving the eigenvalue problem, formulating the probability distribution of peaks applying the Hermite-moment method, and predicting the deck-slamming occurrence. Tension leg platform(TLP) and semi-submersible platform are considered as example models for the application of the present method, and the probability of deck slamming on various points is investigated for several ocean environmental conditions.
In this paper, a semi-analytic method is introduced to predict the deck-slamming probability and corresponding loads. This method is based on a nonlinear statistical approach that takes into account the linear and second-order components of the relative wave elevation up to the second order. The linear and second-order wave elevation is assumed to be a two-term Volterra series. The joint probability density function of the relative wave elevation and velocity are formulated using the Hermite-moment method, and the probability distributions of the wave crest and relative wave velocity are calculated. These probability distributions are verified using the data sampled from the linear and second-order relative wave elevation. Based on this formulation, the probabilities of deck slamming and slamming-induced loads are estimated. This method is applied to a tension leg platform (TLP) model, and the effects of the second-order component of the relative wave elevation on the deck slamming are investigated.
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