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Development of a 6-DOF Dynamic Velocity Prediction Program for offshore racing yachts

Article dans une revue avec comité de lecture
Author
KERDRAON, Paul
232891 Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique [LHEEA]
HOREL, Boris
232891 Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique [LHEEA]
ccBOT, Patrick
13094 Institut de Recherche de l'Ecole Navale [IRENAV]
LETOURNEUR, Adrien
LE TOUZÉ, David
232891 Laboratoire de recherche en Hydrodynamique, Énergétique et Environnement Atmosphérique [LHEEA]

URI
http://hdl.handle.net/10985/20167
DOI
10.1016/j.oceaneng.2020.107668
Date
2020
Journal
Ocean Engineering

Abstract

Thanks to high lift-to-drag ratios, hydrofoils are of great interest for high-speed vessels. Modern sailing yachts fitted with foils have thus reached impressively high speeds on the water. But this hydrodynamic efficiency is achieved at the expense of stability. Accurate tradeoffs are therefore needed to ensure both performance and safety. While usual Velocity Prediction Programs (VPPs) are inadequate to assess dynamic stability, the varying nature of the offshore racing environment further complicates the task. Dynamic simulation in the time-domain is thus necessary to help architects assess their designs. This paper presents a system-based numerical tool which aims at predicting the dynamic behavior of offshore sailing yachts. A 6 degrees of freedom (DOF) algorithm is used, calculating loads as a superposition of several components (hull, appendage, sails). Part of them are computed at runtime while the others use pre-computed dataset, allowing a good compromise between efficiency and flexibility. Three 6DOF simulations of an existing offshore trimaran (a maneuver, unsteady wind conditions and quartering seas) are presented. They underline the interest of dynamic studies, demonstrating how important the yacht state history is to the understanding of her instantaneous behavior and showing that dynamic simulations open a different field of optimization than VPPs.

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