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- W2762723789 abstract "In the assessment of marine structures in shallow waters domain it is important to take into account the nonlinear (or non-Gaussian) nature of the irregular waves when predicting short and long-term responses of such structures. Other sources of nonlinearities in the response are also present due to some nonlinear effects such as: wet-dry surface effects, wind force on dry parts of the structure, drag term in Morison hydrodynamic force equation, etc. The estimation of the characteristic short-term extreme responses requires the extreme value analysis of a non-Gaussian stochastic process. There are many approaches available in literature which can be employed, such as: Hermite-based model, Weibull-fitting model, etc. In this paper two distinct Weibull fitting models (one based on the first two and other based on the first three moments of the response peaks sample) and Hermite-based models using both conventional and linear moments (L-moments) are investigated for the prediction of extreme short-term response of mono-column wind tower installed in a water depth of 20m and subject to wave, current and wind loading. The tower responses (load effects) time-histories are obtained by means of a time-domain finite element-based program using 3-D geometric nonlinear beam elements developed for the dynamic analysis of this type of structure. In this program, the nonlinear behavior of the irregular waves is modelled by means of the second order Sharma and Dean theory [1] and the wind forces are represented by a very simplified load model based on wind velocity simulated time-series and the obstruction area of the tower and blades." @default.
- W2762723789 created "2017-10-20" @default.
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- W2762723789 date "2017-06-25" @default.
- W2762723789 modified "2023-09-27" @default.
- W2762723789 title "Extreme Value Analyses of Dynamic Response Parameters of a Wind Tower Structure Under Short-Term Nonlinear Irregular Seastate" @default.
- W2762723789 doi "https://doi.org/10.1115/omae2017-61495" @default.
- W2762723789 hasPublicationYear "2017" @default.
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