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Abstract-This study addresses the simulation of a class of non-normal processes based on measured samples and sample characteristics of the system input and output. The class of nonnormal processes considered here concerns environmental loads, such as wind and wave loads, and associated structural responses. First, static transformation techniques are used to perform simulations of the underlying Gaussian time or autocorrelationsample. An optimization procedure is employed to overcome errors associated with a truncated Hermite polynomial transformation. This method is able to produce simulations which closely match the sample process histogram, power spectral density, and central moments through fourth order. However, it does not retain the specific structure of the phase relationship between frequency components, demonstrated by the inability to match higher order spectra. A Volterra series up to second order with analytical kernels is employed to demonstrate the bispectral matching made possible with memory models. A neural network system identification model is employed for simulation of output when measured system input is available, and also demonstrates the ability to match higher order spectral characteristics. Copyright c~ 1996 Elsevier Science Ltd.

In an effort to more effectively understand and manage vortex-induced vibration (VIV) fatigue integrity of its drilling risers, BP has instrumented several of them on a number of mobile offshore drilling units (MODUs) and offshore production platforms worldwide. This paper presents several aspects of the findings from those monitoring campaigns, with particular emphasis on the relatively more densely populated MODU data sets. In-situ monitoring has practical use as a realtime quantifier of accrued VIV fatigue damage to both drilling riser and wellhead casing over the course of a given monitoring period, a fundamental indicator of structural integrity. At present, this can be very useful to operators given that the gap between predicted and measured VIV fatigue damage can be very large. In this paper, the measured data are used to expose some of the physical details of full-scale riser response whose omission from predictive design tools and methods may contribute to this wide gap. To characterize the size of the gap, the data are compared to calculations using the most commonly used industry VIV analysis software. This demonstrates the inherent level of analysis over conservatism with respect to full-scale, unsuppressed drilling risers in the field when typical analysis parameters are utilized. A means of adjusting the parameters to reduce the over conservatism is then implemented. Finally, the data are used to reveal some performance indicators for VIV suppression devices that are presently being utilized in drilling operations.