Improvement of Energy Saving Effect for the Stern Duct on JBC Bulk Carrier by using CFD

Abstract

The goal of this study is to improve the duct which is installed in the stern of JBC (Japan Bulk Carrier) and generate its energy-saving effect higher than the original one i e 0 6% The original design of the duct is an axisymmetrical foil section with an angle of attack of 20 06 degrees The grid construction is the particularly important pre-processing of CFD After finding the appropriate parameters and conditions to generate the mesh we continuously used the setting By this way the integrity and consistency can be ensured among the different meshes when extending to the other desired geometry for the simulation Due to the high cost and time-consuming of EFD this study will design a new duct by CFD method without EFD data First two sets of grids based on the related grid construction setting were used to simulate the ship resistance test with and without the original duct and then compared the results with EFD This procedure would establish a reliable simulation method and then extend and apply the simulation method to the newly designed duct In this study the stern flow is analyzed as well Since the grids were established by the same setting and construction method the influence of grid building to CFD results is negligible In other words the grid dependency is satisfied Therefore we can observe clearly the difference caused by different duct to the flow field and resistance By analyzing the results of JBC with OPENFOAM and EFD comparison of resistance value stern wake velocity distribution and wave-making pattern were conducted After comparing with EFD two sets of CFD grid were selected with or without local refinement to design the duct The computational domain boundary condition grid construction setting and the hull geometry input were kept the same Only difference is to change the geometry input of the energy-saving device The simulation results show that the energy-saving effect of this new duct can reach between 2 33% and 2 49%

Date of Award	2020
Original language	English
Supervisor	Ping-Chen Wu (Supervisor)