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微小狭缝肋矩形通道多目标优化

孔德海 陈少秋 刘存良 郭涛

孔德海, 陈少秋, 刘存良, 等. 微小狭缝肋矩形通道多目标优化[J]. 航空动力学报, 2023, 38(5):1025-1037 doi: 10.13224/j.cnki.jasp.20210519
引用本文: 孔德海, 陈少秋, 刘存良, 等. 微小狭缝肋矩形通道多目标优化[J]. 航空动力学报, 2023, 38(5):1025-1037 doi: 10.13224/j.cnki.jasp.20210519
KONG Dehai, CHEN Shaoqiu, LIU Cunliang, et al. Multi-objective optimization of rectangular channel with miniature slit ribs[J]. Journal of Aerospace Power, 2023, 38(5):1025-1037 doi: 10.13224/j.cnki.jasp.20210519
Citation: KONG Dehai, CHEN Shaoqiu, LIU Cunliang, et al. Multi-objective optimization of rectangular channel with miniature slit ribs[J]. Journal of Aerospace Power, 2023, 38(5):1025-1037 doi: 10.13224/j.cnki.jasp.20210519

微小狭缝肋矩形通道多目标优化

doi: 10.13224/j.cnki.jasp.20210519
基金项目: 国家自然科学基金(52006180); 中央高校基础科研基金(3102020OQD702); 国家科技重大专项(2017-Ⅲ-0001-0025)
详细信息
    作者简介:

    孔德海(1988-),男,副教授,博士,主要从事航空发动机热端部件先进冷却技术研究

    通讯作者:

    刘存良(1983-),男,教授、博士生导师,博士,主要从事航空发动机热端部件先进冷却技术和精细化热分析研究。E-mail: liucunliang@nwpu.edu.cn

  • 中图分类号: V232.4

Multi-objective optimization of rectangular channel with miniature slit ribs

  • 摘要:

    开展了矩形通道内微小狭缝肋的换热和流阻性能的多目标优化研究。选取缝宽、相邻缝间距、狭缝的前端面和后端面与壁面距离四个参数作为优化变量,采用非支配排序遗传算法(NSGA-Ⅱ)获得了Pareto 最优解。分析了Pareto最优前沿面上四种优化方案下微小狭缝肋的流动和传热热特性。结果表明:优化后的微小狭缝肋的换热能力与实心肋相当,而流动阻力有所降低,肋壁的换热均匀性得到显著提高。

     

  • 图 1  计算区域和边界条件示意图(单位:mm)

    Figure 1.  Schematic view of the computational domain and boundary conditions (unit: mm)

    图 2  狭缝肋的布置和它的截面形状示意图

    Figure 2.  Schematic diagram of slit rib configuration and its cross-section shape

    图 3  狭缝肋结构全局和局部的六边形网格结构示意图

    Figure 3.  Schematic of structured hexagonal global and local mesh structures of the slit rib

    图 4  不同雷诺数下预测的可穿透微小肋通道相对平均努塞尔数和相对摩擦因子对比

    Figure 4.  Comparisons of the predicted relative average value of the Nusselt numbers and the friction factor for channel with miniature slit ribs at different Re

    图 5  多目标优化程序流程图

    Figure 5.  Flowchart of the multi-objective optimization procedure

    图 6  $\overline{Nu}/\overline{Nu}_0 $f0/f 随运行次数的变化

    Figure 6.  $\overline{Nu}/\overline{Nu}_0 $ and f0/f versus the run counter

    图 7  由NSGA-Ⅱ得到的Pareto前沿

    Figure 7.  Pareto-optimal front searched by the NSGA-Ⅱ

    图 8  狭缝中心流向截面上的流线和流向速度分布(Re=40 000)

    Figure 8.  Streamlines and streamwise velocity contours on the central streamwise plane of the slit (Re=40 000)

    图 9  狭缝中心流向截面上的湍动能分布

    Figure 9.  Contours of turbulence kinetic energy on the central streamwise plane of the slit

    图 10  不同展向截面上的流线和湍动能分布

    Figure 10.  Streamlines and contours of turbulence kinetic energy on various spanwise cross-sections

    图 11  狭缝中心流向截面上的展向涡量分布

    Figure 11.  Contours of span vorticity on the streamwise center plane of the slit

    图 12  展向截面X=0.5h上的流向涡量分布

    Figure 12.  Contours of streamwise vorticity on cross-section X = 0.5h

    图 13  XZ中心截面上第三排肋片附近的温度分布

    Figure 13.  Temperature contours on the XZ central plane of the third rib

    图 14  肋壁表面的相对局部努塞尔数分布

    Figure 14.  Relative local Nusselt number contour on rib walls

    图 15  相对平均努塞尔数、相对摩擦因子和综合热性能随雷诺数的变化

    Figure 15.  Variations of relative averaged Nusselt number, relative friction factor and thermal-hydraulic performance with Re

    表  1  微小扩张型狭缝肋的网格收敛性结果

    Table  1.   Grid convergence results for miniaturediffuser slit rib

    参数$\Delta p $/PaNu
    $\varphi_{1} $1.192100.64
    $\varphi_{2} $1.171101.34
    ${\boldsymbol{}}\varphi_{3} $1.172100.94
    $\varphi_{{\rm{e x t}}}^{21} $1.193100.00
    $e_{ {\rm{e x t} } }^{21}$/%0.0380.64
    $I_{{\rm{gc,fine}}}^{21}$/%0.0480.80
    下载: 导出CSV

    表  2  设计变量和设计空间

    Table  2.   Design variables and design space

    变量基准值/mm最小值/mm最大值/mm
    $L_{0} $20150
    $B_{0} $20150
    $ h_{1}$2.20.13.2
    $h_{2} $0.60.13.2
    下载: 导出CSV

    表  3  Pareto优化设计结果

    Table  3.   Results of Pareto optimal designs

    方案设计变量 目标函数值(Kriging model) 目标函数值(RANS)预测精度误差/%
    L0/mmB0/mmh1/mmh2/mm$\overline{Nu}/\overline{Nu}_{0} $f0/f$\overline{Nu}/\overline{Nu}_{0} $f0/f$\overline{Nu}/\overline{Nu}_{0} $f0/f
    Baseline00001.45140.2853
    Opt 112.335.780.170.511.45080.25521.40950.29142.9312.42
    Opt 212.5049.540.500.391.34650.30601.42650.29425.614.01
    Opt 313.721.500.710.281.39610.26731.39120.29940.3510.72
    Opt 412.3344.890.160.511.37990.29421.41320.29362.360.204
    下载: 导出CSV
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  • 收稿日期:  2021-09-17
  • 网络出版日期:  2022-11-28

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