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Reconstruction et prévision déterministe de houle à partir de données mesurées

Abstract : Wave prediction is a crucial task for offshore operations from an obvious security point of view regarding working people and technical equipments or structures. The prediction tools available since now are based on a stochastic description of the sea state and are not able to predict deterministically the wave fields evolution. Only averaged statistical data representative of the sea state can be obtained from the known spectral quantities. To face the growing need of accurate short term predictions, a deterministic prediction model has been developed in order to improve the efficiency of the sea operations which require a precise knowledge of the sea surface on a specific region of interest. After achieving a theoretical study to determine the available time-space predictable domain depending on the current sea state and on the measurement conditions, we created two data assimilation process to combine the measured observations to the physics-based model. This model is a second order model for low to moderate steeped fields, or a high-order model for high crested seas, namely the High-Order Spectral numerical method. The extended second order model and the third order model using the HOS have been validated for the prediction of 2D synthetic and basin wave fields: the averaged prediction errors we obtain are more than two times less than the errors returned by a linear approach. The improvement is also more important that the steepness and the order of the prediction model are high.
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Contributor : Elise Blondel-Couprie <>
Submitted on : Thursday, January 21, 2010 - 11:58:48 AM
Last modification on : Thursday, January 11, 2018 - 6:17:20 AM
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  • HAL Id : tel-00449343, version 1



Elise Blondel-Couprie. Reconstruction et prévision déterministe de houle à partir de données mesurées. Dynamique des Fluides [physics.flu-dyn]. Ecole Centrale de Nantes (ECN), 2009. Français. ⟨tel-00449343⟩



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