PARAMETRIC MODELING OF STOCHASTIC WAVE EFFECTS ON OFFSHORE PLATFORMS

The time histories of stochastic ocean wave-related processes are simulated by means of computationally efficient parametric models. The parametric models utilized here include the autoregressive and moving averages (ARMA) algorithms for the simulation of wave height fluctuations, discrete convolution models for linear transformations of given time histories, discrete differentiation models for obtaining derivatives, discrete interpolation models for interpolating time series at intermediate time increments and their hybrid combination. The recursive simulation 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 description 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 transformation is employed to simulate derivatives of response processes. A hybrid combination of discrete convolution and differentiation models provides an efficient simulation scheme for evaluating wave loads at the instantaneous position of compliant platforms. Interpolation of time histories is carried out utilizing double subscripted digital filters. The selection of appropriate models and their orders is discussed in the context of their stability, accuracy and robustness. Detailed examples are given to illustrate the practical features of these models.