An investigation into fishing boat optimisation using a hybrid algorithm
An investigation into fishing boat optimisation using a hybrid algorithm
The optimisation of high-speed fishing boats is different from the optimisation of other displacement type vessels as, for high-speed fishing boats, the wave-making resistance decreases while the splashed resistance increases sharply. To reduce fuel consumption and operating costs in the current economic climate, this paper presents a fishing boat optimisation approach using a Computational Fluid Dynamics (CFD) technique. The RANS-VoF solver was utilised to calculate total resistance, sinkage and trim for a fishing boat in calm water. The Arbitrary Shape Deformation (ASD) technique was used to smoothly alter the geometry. A hybrid algorithm was presented to solve the complicated nonlinear optimisation problem. Herein, a Design of Experiments (DoE) method was applied to find an optimal global region and a mathematical programme was employed to determine an optimal global solution. Under the same displacement with the original hull, two optimisation loops were built with different design variables. After completion of the optimisation, two optimal hull forms were obtained. The optimisation results show that the optimisation loop presented in this study can be used to design a suitable fishing boat in the reduction of the total resistance in calm water.
204-220
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
Shenglong, Zhang
13e00584-35b9-4881-8730-e2a3ce2b516b
Demirel, Yigit Kemal
44a59a7c-8ba9-481d-be96-d50c46fbdf34
Liu, Wendi
b5eb4413-e22a-4aba-9489-33f3dfb6cc69
Leping, Xu
ff784147-2415-4ef7-889f-636dbea3efd9
Lai, Yuyang
cb5e4875-bf1f-4277-98a6-b847d6ef792f
Kurt, Rafet Emek
73c05791-ef15-4784-a2ba-f1e95cba790b
Djatmiko, Eko Budi
d770702e-245d-4336-952f-97bc0dbd5a58
Incecik, Atilla
25a12ee2-7ba6-47cf-af5d-a79de4c6a2c4
1 November 2018
Tezdogan, Tahsin
7e7328e2-4185-4052-8e9a-53fd81c98909
Shenglong, Zhang
13e00584-35b9-4881-8730-e2a3ce2b516b
Demirel, Yigit Kemal
44a59a7c-8ba9-481d-be96-d50c46fbdf34
Liu, Wendi
b5eb4413-e22a-4aba-9489-33f3dfb6cc69
Leping, Xu
ff784147-2415-4ef7-889f-636dbea3efd9
Lai, Yuyang
cb5e4875-bf1f-4277-98a6-b847d6ef792f
Kurt, Rafet Emek
73c05791-ef15-4784-a2ba-f1e95cba790b
Djatmiko, Eko Budi
d770702e-245d-4336-952f-97bc0dbd5a58
Incecik, Atilla
25a12ee2-7ba6-47cf-af5d-a79de4c6a2c4
Tezdogan, Tahsin, Shenglong, Zhang, Demirel, Yigit Kemal, Liu, Wendi, Leping, Xu, Lai, Yuyang, Kurt, Rafet Emek, Djatmiko, Eko Budi and Incecik, Atilla
(2018)
An investigation into fishing boat optimisation using a hybrid algorithm.
Ocean Engineering, 167, .
(doi:10.1016/j.oceaneng.2018.08.059).
Abstract
The optimisation of high-speed fishing boats is different from the optimisation of other displacement type vessels as, for high-speed fishing boats, the wave-making resistance decreases while the splashed resistance increases sharply. To reduce fuel consumption and operating costs in the current economic climate, this paper presents a fishing boat optimisation approach using a Computational Fluid Dynamics (CFD) technique. The RANS-VoF solver was utilised to calculate total resistance, sinkage and trim for a fishing boat in calm water. The Arbitrary Shape Deformation (ASD) technique was used to smoothly alter the geometry. A hybrid algorithm was presented to solve the complicated nonlinear optimisation problem. Herein, a Design of Experiments (DoE) method was applied to find an optimal global region and a mathematical programme was employed to determine an optimal global solution. Under the same displacement with the original hull, two optimisation loops were built with different design variables. After completion of the optimisation, two optimal hull forms were obtained. The optimisation results show that the optimisation loop presented in this study can be used to design a suitable fishing boat in the reduction of the total resistance in calm water.
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Accepted/In Press date: 28 August 2018
Published date: 1 November 2018
Identifiers
Local EPrints ID: 479260
URI: http://eprints.soton.ac.uk/id/eprint/479260
ISSN: 0029-8018
PURE UUID: 8d80066e-7faf-46ec-b722-01bae2698fae
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Date deposited: 20 Jul 2023 16:50
Last modified: 17 Mar 2024 04:18
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Author:
Tahsin Tezdogan
Author:
Zhang Shenglong
Author:
Yigit Kemal Demirel
Author:
Wendi Liu
Author:
Xu Leping
Author:
Yuyang Lai
Author:
Rafet Emek Kurt
Author:
Eko Budi Djatmiko
Author:
Atilla Incecik
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