基于多目标优化算法NSGA Ⅱ的极地穿梭油轮型线设计

段菲; 张利军; 陈鸽; 姜海宁; 张琪

doi:10.3969/j.issn.1673-3185.2017.06.010

基于多目标优化算法NSGA Ⅱ的极地穿梭油轮型线设计

doi: 10.3969/j.issn.1673-3185.2017.06.010

中远海运重工有限公司技术研发中心, 辽宁大连 116000

详细信息

作者简介:
张利军, 男, 1977年生, 博士, 高级工程师

陈鸽, 男, 1983年生, 硕士, 工程师

通信作者:
段菲(通信作者), 女, 1990年生, 硕士, 助理工程师

中图分类号: U661.31
计量
- 文章访问数: 418
- HTML全文浏览量: 172
- PDF下载量: 99
- 被引次数: 0
出版历程
- 收稿日期: 2017-05-23
- 网络出版日期: 2017-11-28
- 刊出日期: 2017-12-08

Polar vessel hullform design based on the multi-objective optimization NSGA Ⅱ

Technology R & D Center, COSCO Shipping Heavy Industry CO. LTD, Dalian 116000, China

基于多目标优化算法NSGA Ⅱ的极地穿梭油轮型线设计由段菲，等创作，采用知识共享署名4.0国际许可协议进行许可。

摘要

摘要: 目的随着北极丰富油气资源的不断开采，需要大量满足极地航行要求的船舶。方法将非支配排序遗传算法（NSGA Ⅱ）应用于船体型线优化设计，提出极地船舶多目标优化方法。以船舶无冰静水阻力以及冰区航行阻力为优化目标，通过极地船舶排水量以及船舶能效设计指数EEDI两项标准进行船型筛选，快速实现满足冰区船舶装载量与EEDI排放要求的船型优化。以常规6.5万吨穿梭油轮为研究对象，采用全参数化建模方式，通过极地船舶多目标优化方法分别对3种不同艏部形式的船型进行优化，结果优化后的船型均满足冰区IA级航行要求，其中无冰静水阻力最大减小约12.94%，冰区最小推进功率最大减小约27.36%，结论有效验证了基于NSGA Ⅱ的极地船舶多目标优化方法的可行性与合理性。
- 极地船舶 /
- 多目标优化方法 /
- 非支配排序遗传算法 /
- 船型优化
Abstract: Objectives With the increasing exploitation of the Arctic abundant oil and gas resources, a large number of ships which meet the polar navigational requirements are needed. Methods In this paper, the fast elitist Non-Dominated Sorting Genetic Algorithm (NSGA Ⅱ) is applied to the hull optimization, and the multi-objective optimization method of polar vessel design is proposed. With the optimization goal of resistance and icebreaking resistance, filtering hull forms through the standard of polar vessel displacement and EEDI, fast ship hull optimization that satisfy the ice-ship dead weight and EEDI requirements has been achieved. Taking a 65 000 t shuttle tanker as an example, full parametric modeling method is adopted, the hull optimization of three different bow forms is conducted through the polar vessel multi-objective optimization method. Results The ship hull after optimization can satisfy the IA class navigation require, where the resistance in calm water decreases up to 12.94%, and the minimum propulsion power in ice field has a 27.36% reduction. Conclusions The feasibility and validity of the NSGA Ⅱ applying in polar vessel design is verified.
- polar vessel /
- multi-objective optimization method /
- NSGA Ⅱ /
- hull design

HTML全文

图 1 拥挤度概念示意

Figure 1. Schematic diagram of congestion

下载: 全尺寸图片幻灯片

图 2 基于NSGA Ⅱ算法极地船舶多目标优化方法流程图

Figure 2. Flow chart of multi-objective optimization of polar vessel based on NSGA Ⅱ

下载: 全尺寸图片幻灯片

图 3 船舶主尺度及主要特征参数

Figure 3. The dimensions and main parameters of the ship

下载: 全尺寸图片幻灯片

图 4 全参数化建模

Figure 4. Fully parametric modeling

下载: 全尺寸图片幻灯片

图 5 常规6.5万吨穿梭油轮三维模型

Figure 5. Model of conventional 65 000 t shuttle tanker

下载: 全尺寸图片幻灯片

图 6 不同艏部形式最优船型三维模型

Figure 6. Model of optimal polar vessel hull for different bow types

下载: 全尺寸图片幻灯片

图 7 3种艏部船型横剖线对比图

Figure 7. Section lines of optimal polar vessel hull for different bow types

下载: 全尺寸图片幻灯片

图 8 不同艏部形式最优船型波形图（D=12.5 m，V=14.5 kn）

Figure 8. Waveforms of optimal polar vessel hull for different bow types

下载: 全尺寸图片幻灯片

图 9 不同艏部形式最优船型艏艉压力分布

Figure 9. Pressure distribution of optimal polar vessel hull for different bow types

下载: 全尺寸图片幻灯片

表 1 不同冰级船舶钢重量增加百分比

Table 1. Steel weight increase for different ice classes

Ice classes	Steel weight increase/%
IC	2
IB	4
IA	6
IA Supper	8

下载: 导出CSV

表 2 各船级社冰级符号与FSICR对应关系^[13]

Table 2. Corresponding relations between FSICR and different ice classes of each classification society

Ice classes（FSICR）	h0/m	ABS	BV	CCS	DNV	GL	LR	NK	RINA	RMRS	IACS
IA Super	1.0	IAA	IAS	B1^*	ICE-1A^*	E4	1AS	IA Super	IAS	LU5	PC6
IA	0.8	IA	IA	B1	ICE-1A	E3	1A	IA	IA	LU4	PC7
IB	0.6	IB	IB	B2	ICE-1B	E2	1B	IB	IB	LU3	-
IC	0.4	IC	IC	B3	ICE-1C	E1	1C	IC	IC	LU2	-

下载: 导出CSV

表 3 常规6.5万吨穿梭油轮主尺度及各参数表

Table 3. Main dimensions and parameters of conventional 65 000 t shuttle tanker

参数	数值
总长/m	216.00
垂线间长/m	205.00
船宽/m	36.00
型深/m	19.20
设计吃水/m	12.50
满载吃水/m	13.50
载重（13.50 m）/t	Approx. 65 000
满载吃水处浮心位置/%	+2.37%
设计航速/kn	14.5
最大主机功率/kW	10 200

下载: 导出CSV

表 4 常规6.5万吨及3型极地6.5万吨模型各目标函数值对比表

Table 4. Comparison of each objective function of conventional 6.5×10⁴ t and three optimal polar vessels

Ship model with different bow type	Volume/m³	Residual resistance coefficient C_r	Frictional resistance coefficient C_f	Total resistance R_t /kN	Effective power P_e/kW	Longitudinal center of buoyancy from midship/%	The angle of the waterline at B/4 α（/°）	The rake of the bow at B/4 φ₂ /（°）	Length of the bow L_BOW/m	Area of the waterline of the bow A_wf/m²	Required engine output for ice classes IA P_min/kW	EEDI/ （g·（t·n mile）^-1）
Fig. 6（a）	79 990	0.544 7×10³	2.489×10³	585.46	4 366.8	+2.29	32.6	50.6	40	1 008.86	11 973	5.41
Fig. 6（b）	79 962	0.575 7×10³	2.483×10³	594.65	4 435.4	+2.17	31.5	53.0	37	1 001.19	11 683	5.28
Fig. 6（c）	80 045.1	0.613 3×10³	2.581×10³	605.76	4 518.2	+2.90	27.7	90.0	60	1 814.40	10 206	4.63
Conventional 6.5×10⁴ t model	79 024.4	0.838 5×10³	2.544×10³	672.47	5 015.8	+2.37	38.2	57.0	42	1 081.08	14 050	6.32

下载: 导出CSV

参考文献(14)

[1]	MARKOV N E, SUZUKI K. Hull form optimization by shift and deformation of ship sections[J]. Journal of Ship Research, 2001, 45(2):197-204. https://ynu.pure.elsevier.com/en/publications/hull-form-optimization-by-shift-and-deformation-of-ship-sections
[2]	SAHA G K, SUZUKI K, KAI H. Hydrodynamic optimization of ship hull forms in shallow water[J]. Journal of Marine Science and Technology, 2004, 9(2):51-62. doi: 10.1007/s00773-003-0173-3
[3]	SUZUKI K, KAI H, KASHIWABARA S. Studies on the optimization of stern hull form based on a potential flow solver[J]. Journal of Marine Science and Technology, 2005, 10(2):61-69. doi: 10.1007/s00773-005-0198-x
[4]	ABT C, HARRIES S. A new approach to integration of CAD and CFD for naval architects[C]//6th International Conference on Computer Applications and Information Technology in the Maritime Industries. Cortona:[s.n.], 2007.
[5]	ABT C, HARRIES S, HEIMANN J, et al. From redesign to optimal hull lines by means of parametric modeling[C]//2nd International Euro Conference on Computer and IT Applications in the Maritime Industries. Hamburg, Germany, 2003.
[6]	HARRIES S, ABT C. Formal hydrodynamic optimization of a fast monohull on the basis of parametric hull design[C]//5th International Conference on Fast Sea Transportation. Seattle, Washington, USA:The Society of Naval Architects & Marine Engineers, 1999.
[7]	HARRIES S, TILLIG F, WILKEN M, et al. An integrated approach for simulation in the early ship design of a tanker[C]//10th International Conference on Computer Applications and Information Technology in the Maritime Industries. Berlin, German, 2011.
[8]	KIM H. Multi-objective optimization for ship hull form design[D]. Fairfax, VA:George Mason University, 2009. http://mars.gmu.edu/handle/1920/5620
[9]	TAHARA Y, TOHYAMA S, KATSUI T. CFD-based multi-objective optimization method for ship design[J]. International Journal for Numerical Methods in Fluids, 2006, 52(5):499-527. doi: 10.1002/(ISSN)1097-0363
[10]	DEB K, AGRAWAL S, PRATAP A, et al. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization:NSGA-Ⅱ[C]//Proceedings of the 6th International Conference on Parallel Problem Solving from Nature Vi. Paris, France:Springer, 2000:849-858.
[11]	SRINIVAS N, DEB K. Multi-objective function optimization using non-dominated sorting genetic algorithms[J]. Evolutionary Computation, 1995, 2(3):221-248.
[12]	Finnish-Swedish ice class rules:bulletin No. 13/1.10.2002[S]. Finnish Maritime Administration, 2002.
[13]	IACS. Requirements concerning polar class[S]. IACS, 2006.
[14]	MEPC. 2014 Guidelines on the method of calculation of the attained energy efficiency design index (EEDI) for new ships as amended:MEPC 66/21/Add.1[S]. MEPC, 2014.