TY - JOUR
T1 - Resistance prediction and optimization of Tri-SWACH using hybrid surrogate model with particular consideration of outrigger layout
AU - An, Guangshuo
AU - Xiang, Gong
AU - Xiang, Xianbo
AU - Datla, Raju
N1 - Publisher Copyright:
© 2023 Elsevier Ltd
PY - 2023/10/1
Y1 - 2023/10/1
N2 - Trimarans, as high-performance ships, the complex flow field of which generated by the interaction between the main hull and the outrigger plays a crucial role in its hydrodynamic performance compared with conventional mono-hulls. In this paper, a new framework is proposed for calm water resistance prediction and optimization of a novel Trimaran, Tri-SWACH with particular consideration of its outrigger layouts. Firstly, Through the comparison of calm water resistances for the novel Tri-SWACH hull in semi-constrained state using CFD simulations and model tests, the CFD simulation is verified to be a valid approach to build the database for surrogate model. PRS, BPNN and KRG methods are used to build the hybrid surrogate models. The effect of using different weight calculation strategies are examined. It is found that the hybrid surrogate model established by using the heuristic method shows higher prediction accuracy and generalization ability compared with single surrogate models and other weight calculation strategies. Based on the proposed hybrid surrogate model, the particle swarm algorithm is used to optimize the solution in the design space. The effectiveness of the optimal outrigger layout is verified by comparing with the CFD method. Compared to the worst outrigger layout, the calm water resistance of the optimal outrigger layout can be reduced by 5.12%. Finally, the hydrodynamic mechanism behind the difference of resistance under the initial, optimal, and worst outrigger layouts are revealed by comparing and analyzing the wave-making interference of the main hull and outriggers. The methods and findings of this study can provide theoretical guidance and support for the design and operation of Tri-SWACH.
AB - Trimarans, as high-performance ships, the complex flow field of which generated by the interaction between the main hull and the outrigger plays a crucial role in its hydrodynamic performance compared with conventional mono-hulls. In this paper, a new framework is proposed for calm water resistance prediction and optimization of a novel Trimaran, Tri-SWACH with particular consideration of its outrigger layouts. Firstly, Through the comparison of calm water resistances for the novel Tri-SWACH hull in semi-constrained state using CFD simulations and model tests, the CFD simulation is verified to be a valid approach to build the database for surrogate model. PRS, BPNN and KRG methods are used to build the hybrid surrogate models. The effect of using different weight calculation strategies are examined. It is found that the hybrid surrogate model established by using the heuristic method shows higher prediction accuracy and generalization ability compared with single surrogate models and other weight calculation strategies. Based on the proposed hybrid surrogate model, the particle swarm algorithm is used to optimize the solution in the design space. The effectiveness of the optimal outrigger layout is verified by comparing with the CFD method. Compared to the worst outrigger layout, the calm water resistance of the optimal outrigger layout can be reduced by 5.12%. Finally, the hydrodynamic mechanism behind the difference of resistance under the initial, optimal, and worst outrigger layouts are revealed by comparing and analyzing the wave-making interference of the main hull and outriggers. The methods and findings of this study can provide theoretical guidance and support for the design and operation of Tri-SWACH.
KW - Hybrid surrogate model
KW - Outrigger layout
KW - Resistance Prediction
KW - Resistance optimization
KW - Tri-SWACH
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U2 - 10.1016/j.oceaneng.2023.115239
DO - 10.1016/j.oceaneng.2023.115239
M3 - Article
AN - SCOPUS:85164393278
SN - 0029-8018
VL - 285
JO - Ocean Engineering
JF - Ocean Engineering
M1 - 115239
ER -