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Title
Performance Prediction of a Hard-Chine Planing Hull by Employing Different CFD Models
Type Article
Keywords
planing hulls; calm-water performance; CFD; turbulent f uid motion
Abstract
This paper presents CFD (Computational Fluid Dynamics) simulations of the performance of a planing hull in a calm-water condition, aiming to evaluate similarities and differences between results of different CFDmodels. The key differences between thesemodels are the ways they use to compute the turbulent flow and simulate themotion of the vessel. The planingmotion of a vessel on water leads to a strong turbulent fluid flowmotion, and themovement of the vessel fromits initial position can be relatively significant, which makes the simulation of the problem challenging. Two different frameworks including k-ε and DES (Detached Eddy Simulation) methods are employed to model the turbulence behavior of the fluid motion of the air–water flow around the boat. Vertical motions of the rigid solid body in the fluid domain, which eventually converge to steady linear and angular displacements, are numerically modeled by using two approaches, including morphing and overset techniques. All simulations are performed with a similar mesh structure which allows us to evaluate the differences between results of the applied mesh motions in terms of computation of turbulent air–water flow around the vessel. Through quantitative comparisons, themorphing technique has been seen to result in smaller errors in the prediction of the running trim angle at high speeds. Numerical observations suggest that a DES model can modify the accuracy of the morphing mesh simulations in the prediction of the trim angle, especially at high-speeds. The DES model has been seen to increase the accuracy of the model in the computation of the resistance of the vessel in a high-speed operation, as well. This better level of accuracy in the prediction of resistance is a result of the calculation of the turbulent eddies emerging in the water flow in the downstream zone, which are not captured when a k-ε framework is employed. The morphing approach itself can also increase the accuracy of the resistance prediction.
Researchers sasan tavakoli (Second researcher) , Abbas Dashtimanesh (Third researcher) , prasanta sahoo (Third researcher) , Mihkel Korgesaar (Fourth researcher)