摘要
通过提高海上风电安装船的快速性,可大大缩短海上风电项目的投入周期.如何在装载量不变甚至增大的情况下减小其航行阻力,是亟待解决的一个重点问题.基于自由变形(FFD)技术及计算流体力学(CFD)方法,对目标船型艉部型线进行优化,通过建立设计变量与总阻力的BP神经网络(BPNN)模型,清晰地展现出变量的相关关系,得出了阻力性能优良的船体艉部形状及型线设计方案.通过CFD方法对优化船型进行数值仿真,验证了优化流程的正确性及优化结果的可靠性,为风电安装船的全船型线优化提供了经验与技术支持.
By improving the rapidity of offshore wind turbine installation vessels, the commissioning cycle of offshore wind projects can be greatly reduced. How to reduce its resistance during navigation with a constant or even an increased loading capacity is a key issue that needs to be addressed. Based on the free-form deformation(FFD) technique and computational fluid dynamics(CFD) method, the stern line of the target vessel type is optimized. By establishing a BP neural network(BPNN) model of the design variables and the total drag, the correlation between the variables is clearly shown and a design solution for the stern shape and molded line of the vessel with excellent drag performance is derived. Numerical simulations of the optimized vessel are carried out by CFD method to verify the correctness of the optimization process and the reliability of the optimization results. The study provides experience and technical support for the optimization of the full hull profile of wind turbine installation vessels.
作者
黄亚南
陈蒙乐
司萌
李飞虎
冯珺
HUANG Yanan;CHEN Mengle;SI Meng;LI Feihu;FENG Jun(School of Navigation and Naval Architecture Engineering,Dalian Ocean University,Dalian 116023,China;Center for Marine Ranching Engineering Science Research of Liaoning Province,Dalian Ocean University,Dalian 116023,China)
出处
《大连理工大学学报》
CAS
CSCD
北大核心
2023年第1期61-68,共8页
Journal of Dalian University of Technology
基金
辽宁省自然科学基金指导计划资助项目(2019-ZD-0732)
辽宁省教育厅科研计划资助项目(JL201916)。
关键词
海上风电安装船
型线优化
FFD技术
数值模拟
BP神经网络
offshore wind turbine installation vessel
profile optimization
FFD technique
numerical simulation
BP neural network
