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涡识别技术及其在船用螺旋桨伴流场中的应用

杨琳 郑兴

杨琳, 郑兴. 涡识别技术及其在船用螺旋桨伴流场中的应用. 力学学报, 2022, 54(11): 3032-3041 doi: 10.6052/0459-1879-22-339
引用本文: 杨琳, 郑兴. 涡识别技术及其在船用螺旋桨伴流场中的应用. 力学学报, 2022, 54(11): 3032-3041 doi: 10.6052/0459-1879-22-339
Yang Lin, Zheng Xing. Vortex identification technology and its application in the wake field of marine propeller. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(11): 3032-3041 doi: 10.6052/0459-1879-22-339
Citation: Yang Lin, Zheng Xing. Vortex identification technology and its application in the wake field of marine propeller. Chinese Journal of Theoretical and Applied Mechanics, 2022, 54(11): 3032-3041 doi: 10.6052/0459-1879-22-339

涡识别技术及其在船用螺旋桨伴流场中的应用

doi: 10.6052/0459-1879-22-339
基金项目: 国家重点研究开发项目(2020YFB1506701), 国家自然科学基金(51739001, 51879051), 浙江省远岸风电技术重点实验室开放基金(ZOE20200007)和黑龙江省自然科学基金(LH2020E071)资助
详细信息
    作者简介:

    杨琳, 博士, 主要研究方向: 湍流大涡模拟、转子类器械流场. E-mail: yanglin@hrbeu.edu.cn

  • 中图分类号: O3

VORTEX IDENTIFICATION TECHNOLOGY AND ITS APPLICATION IN THE WAKE FIELD OF MARINE PROPELLER

  • 摘要: 涡识别是很重要的流体问题, 为了在船用螺旋桨伴流场中寻找一种合理的涡识别方法, 本文结合实践, 研究了六种涡识别技术理论, 其中使用Burgers涡流和Lamb-Oseen涡流作了必要的解释, 讨论了各种识别方法的优缺点. 局部低压标准比较直观, 但深究其黏性和非定常影响后, 明显不足; 迹线或流线显然不能满足伽利略不变性, 会使辨别变得混乱; 涡度大小需要规定其阈值, 具有一定不确定性, 且也会识别不是涡的涡片; 速度梯度张量的复特征值也会有识别不出的区域; 速度梯度张量的第二不变量标准和对称张量的第二特征值标准能更好地识别涡核, 这两种标准有时等效. 螺旋桨伴流场的数值模拟是在开源软件OpenFOAM平台上实现的, 湍流大涡模型由一种局部动态方程建模, 此模型优于动态Smagorinsky模型. 最终的结果显示: 对于船用螺旋桨伴流场中的涡, 采用速度梯度张量的第二不变量和对称张量的第二特征值的结果基本一致, 而最小压力标准、流线或迹线标准、涡度值标准和速度张量的复特征值标准都存在一定的缺陷, 不适用于船用螺旋桨伴流场中的涡识别.

     

  • 图  1  螺旋桨几何

    Figure  1.  Geometry of blade, hub and shaft

    图  2  叶片沿径向相对弦长和扭角分布

    Figure  2.  Distributions of relative chord length and twist angle along radial direction

    图  3  计算域及初始边界条件

    Figure  3.  Computational domain and initial boundary conditions

    图  4  网格划分示意

    Figure  4.  View of meshing

    图  5  相对涡度和压力分布(实线为涡度, 虚线为压力, 黑虚线为$ {\omega }_{0} = 1 $, 向下橙紫绿黄蓝$ {\omega }_{0} $分别为$ 2,3, \cdots ,6 $)

    Figure  5.  Relative vorticity and pressure distribution (solid line is vorticity; dotted line is pressure; black dotted line is $ {\omega }_{0} = 1 $; downward orange-purple-green-yellow-blue lines are $ {\omega }_{0} = 2,3, \cdots, 6 $ respectively)

    图  6  Lamb-Oseen涡在不同参考系下的流线(快速点比任何一点的速度都快)

    Figure  6.  Streamline of vortex under different reference systems (the speed at the fast point is faster than that at any point)

    图  7  涡度大小等值面

    Figure  7.  Contours of vorticity magnitude

    图  8  涡核识别$ Q = 0 $

    Figure  8.  Vortex core identification $ Q = 0 $

    图  9  涡核识别$ {\lambda }_{2} = 0 $

    Figure  9.  Vortex core identification $ {\lambda }_{2} = 0 $

    表  1  涡识别方法

    Table  1.   Methods of vortex identification

    No.Criterions of identifying vortex
    1 local minimum pressure
    2 pathline or streamline
    3 vorticity magnitude
    4 complex eigenvalue of tensor $ \boldsymbol{T} $
    5 second invariant $ {\boldsymbol{Q}} $ or kinematic vorticity number $ {N}_{k} $
    6 eigenvalue of sym tensor $\left({\boldsymbol{S} }^{2} + {\boldsymbol{\varOmega } }^{2}\right)$
    下载: 导出CSV

    表  2  计算区不同域网格尺度

    Table  2.   Overall cell scales in different regions of computational domain

    Cell scales for about total 8.5 million cells
    Region 0 (background grid)$ 0.125 D $
    Region 1 (dashed line)$ 0.015\;6 D $
    Region 2 (most refinement)$ 0.007\;81 D $
    下载: 导出CSV

    表  3  基于负$ {\lambda }_{2} $和正$ Q $标准识别涡核对比

    Table  3.   Comparison of vortex core identifing results based on negative $ {\lambda }_{2} $ and positive $ Q $ criteria

    $ {\lambda }_{1} $$ {\lambda }_{2} $$ {\lambda }_{3} $$\displaystyle \sum {\lambda }_{\mathrm{i} }$$ -{\lambda }_{2} $$ + Q $
    $ + $$ - $$ - $$ - $yesyes
    $ + $$ - $$ - $$ + $yesno
    $ + $$ + $$ - $$ - $noyes
    $ + $$ + $$ + $$ + $nono
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-07-26
  • 录用日期:  2022-09-20
  • 网络出版日期:  2022-09-21
  • 刊出日期:  2022-11-18

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