基于数值计算的非常规船型操纵运动建模

doi:10.16183/j.cnki.jsjtu.2024.053

摘要/Abstract

摘要：

为建立某内河船舶的操纵运动模型,以分离型模型为基础,建立基于数值计算的操纵运动模型框架;为获取操纵运动模型的水动力学导数,在数值环境下开展了静态斜拖试验(OTT)和动态圆周运动试验(CMT);提出三次样条插值和最小二乘拟合的混合方法以提升非线性水动力导数的精度,缩尺船模Z形试验和回转试验验证了操纵运动模型的精度.结果表明,采用数值计算与混合方法所建立的操纵运动模型具有良好的精度,可用于内河船舶操纵运动建模.

关键词: 非常规船型, 船舶操纵运动模型, 计算流体动力学, 自航试验

Abstract:

To develop a maneuvering model for a typical unconventional ship, a decoupled modeling approach was adopted as the foundation to construct a numerical calculation based maneuvering model framework. To determine the hydrodynamic derivatives for the maneuvering model, static oblique towing test (OTT) and dynamic circular motion test (CMT) were performed by using numerical simulations to obtain the forces on ship body. To improve the accuracy of nonlinear hydrodynamic derivatives, a hybrid method combining cubic spline interpolation with least squares fitting was proposed. The zigzag and rotation tests of the scaled ship model verified the accuracy of the maneuvering model. The results show that the maneuvering motion model established by numerical calculation and the hybrid method has good accuracy and can be used for modeling unconventional ship maneuvering motion.

Key words: unconventional ship, ship maneuvering model, computational fluid dynamics (CFD), free running model test

中图分类号:

U663

郑茂, 丁世淦, 兰加芬. 基于数值计算的非常规船型操纵运动建模[J]. 上海交通大学学报, 2025, 59(12): 1824-1836.

ZHENG Mao, DING Shigan, LAN Jiafen. Maneuvering Motion Modeling of Unconventional Ship Based on Numerical Calculation[J]. Journal of Shanghai Jiao Tong University, 2025, 59(12): 1824-1836.

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参考文献 23

[1]	HE Z, LIU C, CHU X, et al. Dynamic anti-collision A-star algorithm for multi-ship encounter situations[J]. Applied Ocean Research, 2022, 118: 102995. doi: 10.1016/j.apor.2021.102995 URL
[2]	ABKOWITZ M A. Lectures on ship hydrodynamics-Steering and manoeuvrability[R]. Lyngby, Denmark: Hydro- and Aerodynamics Laboratory, 1964.
[3]	YASUKAWA H, YOSHIMURA Y. Introduction of MMG standard method for ship maneuvering predictions[J]. Journal of Marine Science and Technology, 2015, 20(1): 37-52. doi: 10.1007/s00773-014-0293-y URL
[4]	LAN J, ZHENG M, CHU X, et al. Parameter prediction of the non-linear nomoto model for different ship loading conditions using support vector regression[J]. Journal of Marine Science and Engineering, 2023, 11(5): 903. doi: 10.3390/jmse11050903 URL
[5]	LI S, LIU C, CHU X, et al. Ship maneuverability modeling and numerical prediction using CFD with body force propeller[J]. Ocean Engineering, 2022, 264: 112454. doi: 10.1016/j.oceaneng.2022.112454 URL
[6]	SUKAS O F, KINACI O K, BAL S. System-based prediction of maneuvering performance of twin-propeller and twin-rudder ship using a modular mathematical model[J]. Applied Ocean Research, 2019, 84: 145-162. doi: 10.1016/j.apor.2019.01.008 URL
[7]	张立, 周传明, 陈伟民, 等. 船模阻力CFD结果的不确定度分析[J]. 船海工程, 2020, 49(5): 33-36.
	ZHANG Li, ZHOU Chuanming, CHEN Weimin, et al. Uncertainty analysis of CFD results of standard ship model resistance[J]. Ship & Ocean Engineering, 2020, 49(5): 33-36.
[8]	王建华, 万德成. 船舶操纵运动 CFD 数值模拟研究进展[J]. 哈尔滨工程大学学报, 2018, 39(5): 813-824.
	WANG Jianhua, WAN Decheng. CFD simulations of ship maneuvering motion[J]. Journal of Harbin Engineering University, 2018, 39(5): 813-824.
[9]	WANG J, ZOU L, WAN D. Numerical simulations of zigzag maneuver of free running ship in waves by RANS-overset grid method[J]. Ocean Engineering, 2018, 162: 55-79. doi: 10.1016/j.oceaneng.2018.05.021 URL
[10]	XING T, BHUSHAN S, STERN F. Vortical and turbulent structures for KVLCC2 at drift angle 0, 12, and 30 degrees[J]. Ocean Engineering, 2012, 55: 23-43. doi: 10.1016/j.oceaneng.2012.07.026 URL
[11]	ZHANG S, LIU J, LI S, et al. Impact of bow shapes on hydrodynamic derivatives due to drifting conditions[J]. Ocean Engineering, 2022, 245: 110347. doi: 10.1016/j.oceaneng.2021.110347 URL
[12]	BALAGOPALAN A, TIWARI K, RAMEESHA T V, et al. Manoeuvring prediction of a container ship using the numerical PMM test and experimental validation using the free running model test[J]. Ships and Offshore Structures, 2020, 15(8): 852-865. doi: 10.1080/17445302.2019.1688921 URL
[13]	LIU Y, ZOU L, ZOU Z J, et al. Predictions of ship maneuverability based on virtual captive mode tests[J]. Engineering Applications of Computational Fluid Mechanics, 2018, 12(1): 334-353. doi: 10.1080/19942060.2018.1439773 URL
[14]	YASUKAWA H. Maneuvering hydrodynamic derivatives and course stability of a ship close to a bank[J]. Ocean Engineering, 2019, 188: 106149. doi: 10.1016/j.oceaneng.2019.106149 URL
[15]	ZHANG M, KUJALA P, MUSHARRAF M, et al. A machine learning method for the prediction of ship motion trajectories in real operational conditions[J]. Ocean Engineering, 2023, 283: 114905. doi: 10.1016/j.oceaneng.2023.114905 URL
[16]	WANG Z, ZOU Z, SOARES C G. Identification of ship manoeuvring motion based on nu-support vector machine[J]. Ocean Engineering, 2019, 183: 270-281. doi: 10.1016/j.oceaneng.2019.04.085 URL
[17]	郭海鹏. 基于CFD的双桨双舵船四自由度MMG模型建模及操纵性预报研究[D]. 上海: 上海交通大学, 2019.
	GUO Haipeng. Research on the CFD-based modeling of 4-DOF MMG model and maneuverability prediction for a twin-propeller twin-rudder ship[D]. Shanghai: Shanghai Jiao Tong University, 2019.
[18]	CHEN C, DELEFORTRIE G, LATAIRE E. Effects of water depth and speed on ship motion control from medium deep to very shallow water[J]. Ocean Engineering, 2021, 231: 109102. doi: 10.1016/j.oceaneng.2021.109102 URL
[19]	刘义, 邹早建, 夏立, 等. 基于CFD的内河船深浅水中操纵性预报[J]. 船舶力学, 2021, 25(6): 739-751.
	LIU Yi, ZOU Zaojian, XIA Li, et al. CFD-based manoeuvrability prediction for inland ships in deep and shallow waters[J]. Journal of Ship Mechanics, 2021, 25(6): 739-751.
[20]	贾欣乐, 杨盐生. 船舶运动数学模型——机理建模与辨识建模[M]. 大连: 大连海事大学出版社, 1999.
	JIA Xinle, YANG Yanshen. Ship motion mathematical model: Modeling mechanism modeling and identification[M]. Dalian: Dalian Maritime University Press, 1999.
[21]	谭康力, 谢伟, 解学参, 等. 考虑螺旋桨水动力的双桨船操纵运动数值模拟[J]. 华中科技大学学报, 2023, 51(4): 62-68.
	TAN Kangli, XIE Wei, XIE Xuecan, et al. Numerical simulation for twin-propeller ship maneuvering motion considering hydrodynamic performance of propeller[J]. Journal Huazhong University of Science & Technology (Natural Science Edition), 2023, 51(4): 62-68.
[22]	丁子秦, 代燚, 陈作钢, 等. 船模阻力CFD/EFD预报的不确定度抑制方法[J]. 中国舰船研究, 2023, 18(6): 49-59.
	DING Ziqin, DAI Yan, CHEN Zuogang, et al. Uncertainty suppression methods for CFD/EFD resistance prediction of ship model[J]. Chinese Journal of Ship Research, 2023, 18(6): 49-59.
[23]	吴硕琳, 李亚娟, 邓重阳. 基于PIA的非均匀三次B样条曲线Hermite插值[J]. 计算机学报, 2023, 46(11): 2463-2475.
	WU Shuolin, LI Yajuan, DENG Chongyang. Hermite interpolation of non-uniform cubic B-spline curve based on PIA[J]. Chinese Journal of computers, 2023, 46(11): 2463-2475.

参数	取值
参数	实船	船模
缩尺比, λ	50	1
L_PP/m	106.200	2.1240
B/m	16.600	0.332
d/m	3.100	0.062
菱形系数, C_P	0.675 8	0.675 8
C_b	0.654 5	0.654 5
排水体积, Δ/m³	3 595.6	0.028 8
S_R/m²	5.375	0.002 2
螺旋桨直径, D_P/m	2.16(4叶)	0.043 2(4叶)

试验	Fr	β/(°)	r'
OTT	0.195	±16,±8,±4,±2, ±1,±0.5,0	0
CMT	0.195	0	±0.2,±0.4,±0.6
CMT	0.195	-12,-8,-2,2,4,8,12	0.2,0.4,0.6

网格尺寸	网格数量×10^-6
网格尺寸	OTT	CMT
G₁	2.17	3.86
G₂	1.22	1.93
G₃	0.699	1.06

方法	T₁/s	T₂/s	T₃/s
OTT	0.01	0.02	0.04
CMT	0.01	0.02	0.04

参数	X'		Y'		N'
参数	压力	切应力	压力	切应力	压力	切应力
${S}_{{G}_{1}}$	-0.007 218	-0.023 95	0.027 91	0.001 876	0.016 23	-0.000 102 3
${S}_{{G}_{2}}$	-0.007 6	-0.023 87	0.027 86	0.001 849	0.017 34	-0.000 119 1
${S}_{{G}_{3}}$	-0.008 091	-0.023 78	0.028 98	0.001 724	0.017 82	-0.000 127 6
ε₂₁	5.289 1	-0.335 4	-0.185 4	-1.436 2	0.063 2	-0.843 6
ε₃₂	6.808 3	-0.409 1	3.999 4	-6.675 4	2.787	7.109 2
R_G	0.776 9	0.819 7	-0.046 36	0.215 1	0.022 68	-0.118 7
收敛性	Mon.	Mon.	Osc.	Mon.	Mon.	Osc.
P_G	0.728 5	0.573 5	0	4.433 2	10.925 3	0
${\delta }_{REG}^{*}$	18.415 9	-1.525 2	0	-0.393 7	0.001 5	0
${\delta }_{G}^{*}$	5.282	-0.335 4	0	-1.436 2	0.063 2	0
C_G	0.287 2	0.219 9	0	3.648	43.098 3	0
U_G	44.669 3	3.904 9	1.999 7	2.478 7	0.124 9	3.554 6