潜艇阻力及流场数值仿真策略优化分析

doi:10.16183/j.cnki.jsjtu.2020.327

摘要/Abstract

摘要：

为探寻不同湍流模型对直航潜艇阻力和流场仿真计算的影响,基于STAR-CCM+平台,以标准潜艇模型Sub-off为几何研究对象,采用有限体积法结合10种湍流模型对Sub-off的水动力及流场特征开展数值仿真研究.首先,以LES-Smagorinsky湍流模型开展网格及时间步长收敛性计算.其次,选定合适的网格方案和时间步长,结合10种湍流模型开展特定工况下的仿真计算.最后,利用甄选好的湍流模型分析Sub-off的流场特征.结果表明:10种湍流模型在潜艇的水动力性能及流场特征的预报方面存在较大差异, LES-Smagorinsky湍流模型不仅能较好地预报潜艇的水动力性能及流场平均量,还能准确预报流场的二次量.

关键词: 湍流模型, 潜艇, 水动力性能, 流场特征

Abstract:

In order to explore the influence of different turbulence models on the resistance and flow field of an advancing submarine, based on the STAR-CCM+platform, and taking Sub-off as the geometric model, this paper adopts the finite volume method, combing 10 turbulence models to conduct numerical research on hydrodynamic and flow field characteristics of Sub-off. First, the LES-Smagorinsky turbulence model is used for the convergence of grids and time steps. Then, the appropriate grid and time step are selected to calculate 10 kinds of turbulence models in specific cases. Finally, the selected turbulence model is used to analyze the hydrodynamic characteristics and flow fields of Sub-off. The results show that there are great differences among the 10 turbulence models in the prediction of submarine hydrodynamic performance and flow field characteristics. LES-Smagorinsky can not only predict the hydrodynamic performance and the average flow field of submarine, but also accurately predict secondary variables of flow fields.

Key words: turbulence model, submarine, hydrodynamic performance, flow field characteristics

中图分类号:

U661.1

李鹏, 王超, 孙华伟, 郭春雨. 潜艇阻力及流场数值仿真策略优化分析[J]. 上海交通大学学报, 2022, 56(4): 506-515.

LI Peng, WANG Chao, SUN Huawei, GUO Chunyu. Numerical Simulation Strategy Optimization Analysis of Submarine Resistance and Flow Field[J]. Journal of Shanghai Jiao Tong University, 2022, 56(4): 506-515.

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参考文献 19

[1]	毕毅, 高霄鹏, 王波, 等. 潜艇水动力噪声的自航模试验技术研究[J]. 海军工程大学学报, 2007, 19(5): 40-43.
	BI Yi, GAO Xiaopeng, WANG Bo, et al. Acoustic test technique for submarine using remote submersible model[J]. Journal of Naval University of Engineering, 2007, 19(5): 40-43.
[2]	PAN Y C, ZHANG H X, ZHOU Q D. Numerical simulation of unsteady propeller force for a submarine in straight ahead sailing and steady diving maneuver[J]. International Journal of Naval Architecture and Ocean Engineering, 2019, 11(2): 899-913. doi: 10.1016/j.ijnaoe.2019.04.002 URL
[3]	POSA A, BALARAS E. A numerical investigation of the wake of an axisymmetric body with appendages[J]. Journal of Fluid Mechanics, 2016, 792: 470-498. doi: 10.1017/jfm.2016.47 URL
[4]	YAO H L, ZHANG H X, LIU H T, et al. Numerical study of flow-excited noise of a submarine with full appendages considering fluid structure interaction using the boundary element method[J]. Engineering Analysis with Boundary Elements, 2017, 77: 1-9. doi: 10.1016/j.enganabound.2016.12.012 URL
[5]	王超, 郑小龙, 李亮, 等. Y +值对潜艇流场大涡模拟计算精度的影响[J]. 华中科技大学学报(自然科学版), 2015, 43(4): 79-83.
	WANG Chao, ZHENG Xiaolong, LI Liang, et al. Influence of Y + on the calculation of submarine flow field characteristics of LES calculation accuracy [J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2015, 43(4): 79-83.
[6]	FU S, XIAO Z X, CHEN H X, et al. Simulation of wing-body junction flows with hybrid RANS/LES methods[J]. International Journal of Heat and Fluid Flow, 2007, 28(6): 1379-1390. doi: 10.1016/j.ijheatfluidflow.2007.05.007 URL
[7]	李士强, 肖昌润, 曹植珺. 基于STAR-CCM+的潜艇尾流场及水动力数值分析[J]. 中国舰船研究, 2018, 13(Sup.1): 29-35.
	LI Shiqiang, XIAO Changrun, CAO Zhijun. Numerical analysis of wake flow and hydrodynamics for a submarine based on STAR-CCM+[J]. Chinese Journal of Ship Research, 2018, 13(Sup.1): 29-35.
[8]	李士强, 肖昌润. 基于STAR-CCM+的潜艇舵翼水动力性能研究[J]. 舰船科学技术, 2019, 41(11): 37-42.
	LI Shiqiang, XIAO Changrun. Research on hydrodynamic performance of submarine rudder wing based on STAR-CCM+[J]. Ship Science and Technology, 2019, 41(11): 37-42.
[9]	GROVES N, HUANG T, CHANG M. Geometric characteristics of DARAPA Sub-off models[R]. Maryland, USA: David Taylor Naval Ship R&D Center, 1989.
[10]	LI H, THOMAS T. Summary of DARPA Sub-off experimental program data [R]. Maryland, USA: David Taylor Naval Ship R&D Center, 1998.
[11]	HUANG T, LIU H, GROVES N, et al. Measurements of flows over an axisymmetric body with various appendages in a wind tunnel: The DARPA Sub-off experimental program[J]. [C]//Proceedings of 19th Symposium on Naval Hydrodynamics. Seoul, Korea: National Academic Press, 1992.
[12]	KUMAR P, MAHSH K. Large eddy simulation of propeller wake instabilities[J]. Journal of Fluid Mechanics, 2017, 814: 361-396. doi: 10.1017/jfm.2017.20 URL
[13]	胡健, 耿冲, 冯峰. 基于大涡模拟的螺旋桨梢涡数值分析[J]. 华中科技大学学报(自然科学版), 2017, 45(11): 68-73.
	HU Jian, GENG Chong, FENG Feng. Numerical analysis of propeller tip vortex based on large eddy simulation[J]. Journal of Huazhong University of Science and Technology (Natural Science Edition), 2017, 45(11): 68-73.
[14]	SHARIATI S K, MOUSAVIZADEGAN S H. The effect of appendages on the hydrodynamic characteristics of an underwater vehicle near the free surface[J]. Applied Ocean Research, 2017, 67: 31-43. doi: 10.1016/j.apor.2017.07.001 URL
[15]	STERN F, WILSON R V, COLEMAN H W, et al. Comprehensive approach to verification and validation of CFD simulations—Part 1: Methodology and procedures[J]. Journal of Fluids Engineering, 2001, 123(4): 793-802. doi: 10.1115/1.1412235 URL
[16]	JONES D A, CLARKE D B. Simulation of a wing-body junction experiment using the fluent code[R]. Victoria, Australia: DSTO Platforms Sciences Laboratory, 2005.
[17]	ÖLÇMEN S M, SIMPSON R L. Some features of a turbulent wing-body junction vortical flow[J]. International Journal of Heat and Fluid Flow, 2006, 27(6): 980-993. doi: 10.1016/j.ijheatfluidflow.2006.02.019 URL
[18]	ROACHE P J. Quantification of uncertainty in computational fluid dynamics[J]. Annual Review of Fluid Mechanics, 1997, 29(1): 123-160. doi: 10.1146/annurev.fluid.29.1.123 URL
[19]	HUNT J C R, WRAY A A, MOIN P. Eddies, streams, and convergence zones in turbulent flows [C]//Center for Turbulence Research Proceedings of the Summer Program 1988. New York, USA: Standford University Center for Turbulence Research, 1988.

网格方案	围壳表面/个	尾舵表面 (单个舵)/个	艇体表面/个	计算域/ 个
1	9800	2600	267000	6930000
2	11600	3100	294000	8130000
3	13000	4100	311000	9820000
4	15100	5300	352000	12000000

评判系数	方案1/个	方案2/个	方案3/个	方案4/个
1000C_R	1.133	1.156	1.169	1.175
1000C_R	0.962	0.974	0.984	0.989
1000C_R	0.171	0.182	0.185	0.186

网格方案	参数	1000C_R	1000C_R_V	1000C_Rp
1~3	K	0.565	0.833	0.273
	P	1.646	0.526	3.749
	I	0.021	0.063	0.001
2~4	K	0.462	0.500	0.333
	P	2.231	2.000	3.170
	I	0.006	0.006	0.001

时间步长/s	1000C_R	1000C_R_V	1000C_Rp
0.0001	1.162	0.982	0.180
0.0005	1.164	0.983	0.181
0.0010	1.169	0.984	0.185
0.0050	1.175	0.987	0.188

湍流模型	总阻力/N	黏性阻力/N	黏性阻力占总阻力比值/%	压差阻力/N	压差阻力占总阻力比值/%
LES-S	33.617	5.322	15.8	28.295	84.2
LES-W	11.727	4.551	38.8	7.716	61.2
LES-DS	12.311	4.914	39.9	7.397	60.1
DES-SA	34.411	4.783	13.9	29.628	86.1
DES-EBKE	32.632	4.736	14.5	27.896	85.5
DDES	31.133	4.827	15.5	26.306	84.5
IDDES	30.328	4.843	16.0	25.485	84.0
RANS-k-ω	34.403	5.138	14.9	29.265	85.1
RANS-k-ε	31.137	4.772	15.3	26.365	84.7
RANS-SA	35.265	4.899	13.9	30.366	86.1