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基于NSGA-Ⅱ算法的小弯管冲击冷却多目标优化

赵鸿华 宋双文 王志凯

赵鸿华, 宋双文, 王志凯. 基于NSGA-Ⅱ算法的小弯管冲击冷却多目标优化[J]. 航空动力学报, 2024, 39(6):20210688 doi: 10.13224/j.cnki.jasp.20210688
引用本文: 赵鸿华, 宋双文, 王志凯. 基于NSGA-Ⅱ算法的小弯管冲击冷却多目标优化[J]. 航空动力学报, 2024, 39(6):20210688 doi: 10.13224/j.cnki.jasp.20210688
ZHAO Honghua, SONG Shuangwen, WANG Zhikai. Multi-objective optimization of impingement cooling of concave wall based on NSGA-Ⅱ algorithm[J]. Journal of Aerospace Power, 2024, 39(6):20210688 doi: 10.13224/j.cnki.jasp.20210688
Citation: ZHAO Honghua, SONG Shuangwen, WANG Zhikai. Multi-objective optimization of impingement cooling of concave wall based on NSGA-Ⅱ algorithm[J]. Journal of Aerospace Power, 2024, 39(6):20210688 doi: 10.13224/j.cnki.jasp.20210688

基于NSGA-Ⅱ算法的小弯管冲击冷却多目标优化

doi: 10.13224/j.cnki.jasp.20210688
详细信息
    作者简介:

    赵鸿华(1993−),男,工程师,博士生,主要从事航空发动机燃烧室设计的研究

  • 中图分类号: V231.1

Multi-objective optimization of impingement cooling of concave wall based on NSGA-Ⅱ algorithm

  • 摘要:

    为了获得不同冲击孔径(IA),冲击孔流向间距(IFD)和冲击孔展向间距(ISD)耦合作用对回流燃烧室小弯管冲击冷却特性及结构热应力的影响,开展了数值计算(CFD)及有限元分析(FEA)。选择试验设计(DOE)中的最优拉丁超立方(Opt LHD)采样确定了设计空间中的样本点,构建了高精度径向基神经网络模型,并基于改进非劣类(NSGA-Ⅱ)算法对综合冷却效率,壁温分布不均匀系数以及壁面最大热应力进行了多目标寻优,结果表明:综合冷却效率,壁温分布不均匀系数和壁面最大热应力随流向展向间距比、流向间距孔径比和展向间距孔径比的增大而减小;通过多目标NSGA-Ⅱ算法获得了小弯管冲击冷却结构Pareto前沿的3个目标函数值的范围为壁面最大热应力不大于5 MPa,综合冷却效率不小于0.66,壁温分布不均匀系数不大于0.16;小弯管冲击冷却综合最优结构的组合为:冲击孔径为0.94 mm,冲击孔流向间距为4.04 mm,冲击孔展向间距为5.45 mm。

     

  • 图 1  小弯管冲击冷却结构参数

    Figure 1.  Impingement cooling structure parameter of concave wall

    图 2  CFD计算域结构

    Figure 2.  CFD computational domain structure

    图 3  周期性计算域选取

    Figure 3.  Periodic computing domain selection

    图 4  网格无关性验证

    Figure 4.  Grid independence verification

    图 5  不同S/di方案η/ηmax试验与数值计算结果对比

    Figure 5.  Comparison of η/ηmax experimental results and numerical calculation results for different S/di cases

    图 6  不同P/di方案η/ηmax试验与数值计算结果对比

    Figure 6.  Comparison of η/ηmax experimental results and numerical calculation results for different P/di cases

    图 7  小弯管冲击冷却结构气流流动方向

    Figure 7.  Concave wall impingement cooling structure air flow direction

    图 8  不同结构参数耦合作用对综合冷却效率及结构热应力的影响

    Figure 8.  Influences of coupling effects of different structural parameters on comprehensive cooling efficiency and structural thermal stress

    图 9  RBF模型误差分析

    Figure 9.  Error analysis of RBF model

    图 10  Pareto前沿和优化解

    Figure 10.  Pareto front and optimization solution

    表  1  小弯管冲击冷却计算方案

    Table  1.   Impingement cooling numerical procedure of concave wall

    序号 di/mm S/mm P/mm 方案 备注
    1 5 5 Base
    2 1 3.18 7.86 S/P=0.4 相同di
    不同S/P
    3 4.48 5.58 S/P=0.8
    4 5.48 4.56 S/P=1.2
    5 6.32 3.96 S/P=1.6
    6 1.25 5 7.71 S/di=4.0 相同S
    不同S/di
    7 0.83 3.52 S/di=6.0
    8 0.71 2.62 S/di=7.0
    9 0.63 2.0 S/di=8.0
    10 1.25 7.71 5 P/di=4.0 相同P
    不同P/di
    11 0.83 3.52 P/di=6.0
    12 0.71 2.62 P/di=7.0
    13 0.63 2.0 P/di=8.0
    下载: 导出CSV

    表  2  CFD计算边界条件

    Table  2.   CFD boundary conditions

    参数取值
    主流温度Tg/K473.15
    主流进口速度Vg/(m/s)25
    次流温度Tc/K300
    次流进口压力ptci/Pa5000
    下载: 导出CSV

    表  3  DOE方案各结构参数取值范围

    Table  3.   DOE scheme structure parameter range mm

    结构参数 取值范围
    冲击孔径di 0.6~1.2
    流向间距S 2~8
    展向间距P 2~8
    下载: 导出CSV

    表  4  约束变量及其变化范围

    Table  4.   Constrain variables and their range of variation mm

    约束变量 上限 下限
    di 0.4 2.0
    S 2 10
    P 2 10
    下载: 导出CSV

    表  5  优化结果与CFD/FEA结果对比

    Table  5.   Optimization results are compared with the CFD/FEA results

    方法 di/mm S/mm P/mm η δ σ/MPa
    Opt0.944.045.450.6630.1373.902
    CFD/FEA0.6570.1344.016
    误差率/%0.912.24−2.84
    下载: 导出CSV
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出版历程
  • 收稿日期:  2021-12-01
  • 网络出版日期:  2024-01-24

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