|
|
Publicações
Guedes Soares, C., Scotto, M. e Cavaco, P. (1998), “Linear and Non-Linear Models of Long-Term Time Series of Wave Data”, Proceedings of the 17th International Conference on Offshore Mechanics and Arctic Engineering, C. Guedes Soares (Eds.), ASME, New York, Vol. II
Models of long-term time series of sea state parameters are important for the planning of various offshore operations that have durations on the order of some days. In this cases the correlation that exists among the parameters of the successive sea states are very important for the outcome of the operation. The probabilistic models that describe the long term probability of occurrence of sea parameters are not appropriate for this purpose because they do not model the correlation that exists in the sea states time series. Earlier work on the use of linear auto regressive models has demonstrated their ability to describe the second order statistical moments of the sea state time series. Some solutions have been proposed to fill the missing observations in the time series and they have different ranges of applicability. This paper reviews those results and presents new results on the use of bivariate models of significant wave height and mean period and on non-linear models.
Se nao conseguiu obter uma copia desta publicação: Peça uma cópia desta publicação
Para informação sobre todas as publicações do CENTEC pode descarregar: Lista Completa de Publicações do CENTEC
|