﻿ 串列螺旋桨水动力性能的数值预报
 舰船科学技术  2016, Vol. 38 Issue (3): 10-13 PDF

Numerical prediction of the propeller's hydrodynamics performance
WANG Guo-liang, WANG Chao, QIAO Yue, LI Xiang
Golloge of Shipbuilding Engineering, Harbin Engineering University, Harbin 150001, China
Abstract: In order to simulate numerically the tandem propeller hydrodynamics performance of steady viscous flow, the computational fluid dynamics (CFD) method based to the Reynolds-averaged navier-stokes (RANS) equation and the moving reference frame technique is used in the paper. A 3D model of tandem propeller is built according to the points of propeller were calculated by Fortran program and optimized by the method of NURBS. such as thrust coefficients, torque coefficients and the velocity distribution. The computed results agree well with the experimental data such as thrust coefficients, torque coefficients and the velocity distribution. It shows that the numerical method has good accuracy in the prediction of tandem propeller open-water performance.
Key words: tandem propeller    hydrodynamic performance    CFD    viscous flow    numerical simulation
0 引言

1 数学模型 1.1 控制方程

 $\frac{{\partial {u_i}}}{{\partial {x_i}}} = 0,$ (1)
 $\rho \frac{{\partial ({u_i}{u_j})}}{{\partial {x_j}}} = - \frac{{\partial P}}{{\partial {x_j}}} + \rho {g_i} + {\text{ }}\rho \frac{\partial }{{\partial {x_j}}}[\mu (\frac{{\partial {u_i}}}{{\partial {x_j}}} + \frac{{\partial {u_j}}}{{\partial {x_i}}}) - \overrightarrow {{u_i}'{u_j}'} ].$ (2)

1.2 湍流模型的选取

RNG k-ε 模型是由 Yakhot 和 Orzag 把重整化群（RNG）方法引入到湍流研究中建立的一个新的湍流模型，其方程如下：

 $\frac{\partial }{{\partial t}}(\rho k) + \frac{\partial }{{\partial {x_i}}}(\rho k{u_i}) = \frac{\partial }{{\partial {x_j}}}\left[{{\alpha _k}{\mu _{eff}}\frac{{\partial k}}{{\partial {x_j}}}} \right] + {G_k} + \rho \varepsilon ,$ (3)
 $\frac{\partial }{{\partial t}}(\rho \varepsilon ) + \frac{\partial }{{\partial {x_i}}}(\rho \varepsilon {u_i}) = \frac{\partial }{{\partial {x_j}}}\left[{{\alpha _\varepsilon }{\mu _{eff}}\frac{{\partial \varepsilon }}{{\partial {x_j}}}} \right] + {\text{ }}C_{1\varepsilon }^*\frac{\varepsilon }{k}{G_k} - {C_{2\varepsilon }}\rho \frac{{{\varepsilon ^2}}}{k},$ (4)
 ${\mu _{eff}} = \mu + {\mu _t},$ (5)

 ${\mu _t} = \rho {C_\mu }\frac{{{k^2}}}{\varepsilon }.$ (6)
2 数值计算过程

 图 1 螺旋桨三维图 Fig. 1 The three dimension chart of the propeller

 图 2 螺旋桨桨叶与桨毂网格划分 Fig. 2 Grid division of blade and hub
3 数值计算结果 3.1 敞水性能曲线计算结果及与试验的对比

 图 3 螺旋桨的敞水性能曲线 Fig. 3 The curves of propeller’s open water performance
3.2 旋转域内各剖面处的速度分布

 图 4 切向速度分布 Fig. 4 Tangential velocity distribution

 图 5 轴向速度分布 Fig. 5 Axial velocity distribution
4 结语

1）与实验数据的比较可以发现，在螺旋桨的工作点附近，无论是推力系数还是扭矩系数，计算结果都和试验数据吻合很好，表明 CFD 技术对串列螺旋桨敞水性能的计算有较高的预报精度，能较好地满足工程需要。

2）对于进速系数大于 0.9 的情况下，螺旋桨负载较小，推力系数和转矩系数的计算结果更接近于试验值，具有更高的准确性。

3）串列螺旋桨前桨的旋转使水流的运动状态从直线流动变为边流动边旋转，因而使后桨的来流得到周向加速，所以后桨相对于水流来说周向速度明显小于前桨 ，即相对转速低于前桨。

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