Parametric modelling of stochastic wave effects on offshore platforms

The time histories of stochastic ocean wave-related processes are simulated by means of computatlonally efficient parametric models The parametric models utdlzed here include the autoregresslve and moving averages (ARMA) algorithms for the simulation of wave height fluctuations, discrete convolution models for linear transformations of given time histories, discrete differentlatmn models for obtaining denvatwes, discrete interpolation models for interpolating time series at intermediate time increments and their hybrid combination. The recurswe simulatmn of fluctuation in wave height Is accomplished by ARMA algorithm based on a two-stage model-fitting approach that provides simulated processes consistent with the prescribed spectral descriptions The sensitivity of the model order to the wave spectral descnptmn is presented The parametric simulation schemes of linearly related processes, e,g wave load effects, are conducted by means of discrete convolution models utilizing finite and infinite wave forms. A parametric model representing differentiation in the context of a linear transformatmn is employed to simulate derivatives of response processes. A hybrid combination of discrete convolutmn and dlfferentmtion models provides an efficient simulation scheme for evaluating wave loads at the instantaneous posmon of comphant platforms. Interpolation of time histories is carned out utilizing double subscripted digital filters The selectmn of appropriate models and their orders is chscussed m the context of their stabdlty, accuracy and robustness. Detmled examples are given to illustrate the practical features of these models