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可变弯度翼身融合布局气动特性分析与设计

王雨桐 蓝庆生 周铸 杨体浩 宋超

王雨桐,蓝庆生,周铸,等. 可变弯度翼身融合布局气动特性分析与设计[J]. 北京航空航天大学学报,2024,50(4):1292-1307 doi: 10.13700/j.bh.1001-5965.2022.0493
引用本文: 王雨桐,蓝庆生,周铸,等. 可变弯度翼身融合布局气动特性分析与设计[J]. 北京航空航天大学学报,2024,50(4):1292-1307 doi: 10.13700/j.bh.1001-5965.2022.0493
WANG Y T,LAN Q S,ZHOU Z,et al. Design and aerodynamic analysis of blended wing body with variable camber technology[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(4):1292-1307 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0493
Citation: WANG Y T,LAN Q S,ZHOU Z,et al. Design and aerodynamic analysis of blended wing body with variable camber technology[J]. Journal of Beijing University of Aeronautics and Astronautics,2024,50(4):1292-1307 (in Chinese) doi: 10.13700/j.bh.1001-5965.2022.0493

可变弯度翼身融合布局气动特性分析与设计

doi: 10.13700/j.bh.1001-5965.2022.0493
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    通讯作者:

    E-mail:f_yforever@126.com

  • 中图分类号: V221.41+

Design and aerodynamic analysis of blended wing body with variable camber technology

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  • 摘要:

    变弯度机翼在提高常规布局客机气动特性方面有较大的潜力,但也会引起全机俯仰力矩变化,考虑翼身融合布局飞行器力臂短、配平阻力较大的特点,研究变弯度技术在翼身融合布局飞行器上的减阻收益与配平惩罚。从工程实际出发,采用基于舵面偏转的方式实现后缘变弯度并对比分析不同展向位置处舵面的配平能力;然后利用全局优化方法开展变弯度气动减阻优化设计;最后对变弯度设计空间进行探索。结果表明:随着升力系数的改变,产生配平阻力最小的舵面位置也会发生变化。当不考虑俯仰力矩配平约束时,采用变弯度技术至多可以获得4.62%的减阻收益;在考虑俯仰力矩配平约束后,相比于采用中央体后缘舵面配平,采用变弯度技术至少能够减小2.4×10−4的配平损失。不同升力系数下,变弯度的舵面偏转组合方式存在明显差异,小升力系数下,多个舵面负偏的变弯度组合有利于减阻并增加抬头力矩;而大升力系数下则是通过多个舵面正偏的组合实现减阻,但会导致低头力矩增加。基于多舵面组合偏转的变弯度减阻收益与力矩惩罚评估,能为工程上设计可变弯度翼身融合布局飞行器提供参考。

     

  • 图 1  M6机翼网格示意图

    Figure 1.  Schematic diagram of M6 wing grid

    图 2  M6 机翼计算结果与实验数据对比

    Figure 2.  Comparison of M6 wing calculation results with experimental data

    图 3  NSGA-Ⅱ工作原理流程[20]

    Figure 3.  Working principle flow of NSGA-Ⅱ[20]

    图 4  优化设计系统流程图

    Figure 4.  Flowchart of optimization design system

    图 5  舵面划分及剖面布置示意图

    Figure 5.  Schematic diagram of flap division and section layout

    图 6  后缘偏转的FFD 控制体

    Figure 6.  FFD control volume for trailing-edge deflection

    图 7  优化网格及FFD控制体

    Figure 7.  Optimized grid and FFD control volume

    图 8  $Ma = 0.84,\;{C_L} = 0.19$基准构型表面压力及流线图

    Figure 8.  Surface pressure and streamline diagram of baseline configuration ($Ma = 0.84,\;{C_L} = 0.19$)

    图 9  $Ma = 0.84,\;{C_L} = 0.19$基准构型剖面压力系数

    Figure 9.  Pressure coefficient of baseline configuration ($Ma = 0.84,\;{C_L} = 0.19$)

    图 10  各舵单偏时阻力与俯仰力矩变化曲线

    Figure 10.  Curves of drag and pitching moment variation when each flap deflects independently

    图 11  ${C_L} = 0.14$时基准构型与单舵面配平构型对比

    Figure 11.  Comparison of baseline configuration and single flap trim configuration (${C_L} = 0.14$)

    图 12  ${C_L} = 0.24$时基准构型与单舵面配平构型对比

    Figure 12.  Comparison of the baseline configuration and single flap trim configuration(${C_L} = 0.24$)

    图 13  ${C_L} = 0.14$时不考虑俯仰配平时变弯度前后对比

    Figure 13.  Comparison of the baseline configuration and variable camber configuration without considering pitch trim (${C_L} = 0.14$)

    图 14  ${C_L} = 0.24$时不考虑俯仰配平时变弯度前后对比

    Figure 14.  Comparison of baseline configuration and variable camber configuration without considering pitch trim (${C_L} = 0.24$)

    图 15  ${C_L} = 0.14$时中央体后缘配平与变弯度配平对比

    Figure 15.  Comparison of central body trailing edge trim configuration and variable camber trim configuration (${C_L} = 0.14$)

    图 16  ${C_L} = 0.24$时中央体后缘配平与变弯度配平对比

    Figure 16.  Comparison of central body trailing edge trim configuration and variable camber trim configuration (${C_L} = 0.24$)

    图 17  ${C_L} = 0.14$多目标优化pareto前沿

    Figure 17.  Multi-objective optimization pareto frontier (${C_L} = 0.14$)

    图 18  ${C_L} = 0.24$多目标优化pareto前沿

    Figure 18.  Multi-objective optimization pareto frontier (${C_L} = 0.24$)

    图 19  ${C_L} = 0.14$时PCA降维后不同组合舵偏下气动阻力及俯仰力矩系数变化云图

    Figure 19.  Contour of aerodynamic drag and pitch moment coefficients under different combinations of flap deflection after PCA dimension reduction (${C_L} = 0.14$)

    图 20  ${C_L} = 0.24$时PCA降维后不同组合舵偏下气动阻力及俯仰力矩系数变化云图

    Figure 20.  Contour of aerodynamic drag and pitch moment coefficients under different combinations of flap deflection after PCA dimension reduction (${C_L} = 0.24$)

    表  1  基准构型气动力系数

    Table  1.   Aerodynamic coefficient of baseline configuration

    α/(°) ${C_L}$ ${C_D}$ ${C_M}$ L/D
    2.58 0.14 0.00795 0.0040 17.62
    3.12 0.19 0.00904 0.0001 21.00
    3.63 0.24 0.01148 −0.0049 20.91
    下载: 导出CSV

    表  2  ${C_L} = 0.14$时基准构型与单舵面配平构型气动力系数

    Table  2.   Aerodynamic coefficient of baseline configuration and single flap trim configuration (${C_L} = 0.14$)

    布局 舵 0/(°) 舵 1/(°) 舵 2/(°) 舵 3/(°) 舵 4/(°) 舵 5/(°) α/(°) ${C_D}$ ${C_M}$ $\Delta {C_D}$/10−4
    基准构型 0 0 0 0 0 0 2.58 0.00795 0.0040 0
    舵0 配平 4.91 0 0 0 0 0 2.41 0.00817 0.0003 2.2
    舵5 配平 0 0 0 0 0 3.83 2.37 0.00806 0.0001 1.1
    下载: 导出CSV

    表  3  ${C_L} = 0.24$时基准构型与单舵面配平构型气动力系数

    Table  3.   Aerodynamic coefficient of baseline configuration and single flap trim configuration (${C_L} = 0.24$)

    布局 舵 0/(°) 舵 1/(°) 舵 2/(°) 舵 3/(°) 舵 4/(°) 舵 5/(°) α/(°) ${C_D}$ ${C_M}$ $\Delta {C_D}$/10−4
    基准构型 0 0 0 0 0 0 3.63 0.01148 −0.0049 0
    舵0 配平 −5.89 0 0 0 0 0 3.82 0.01228 −0.0001 8
    舵2 配平 0 0 −2.11 0 0 0 3.93 0.01211 −0.0001 6.3
    下载: 导出CSV

    表  4  设计点Kriging代理模型精度验证结果

    Table  4.   Results of validation for Kriging model under design point

    气动性能 最大预测误差 平均预测误差
    ${C_L}$ 6.3×10−4 2.5×10−4
    ${C_D}$ 1.2×10−4 6.8×10−4
    ${C_M}$ 7.6×10−4 2.9×10−4
    下载: 导出CSV

    表  5  不考虑俯仰配平时变弯度减阻优化结果

    Table  5.   Results of variable camber drag reduction optimization without considering pitch trim

    ${C_L}$ 舵 0/(°) 舵 1/(°) 舵 2/(°) 舵 3/(°) 舵 4/(°) 舵 5/(°) α/(°) ${C_D}$ ${C_M}$ $\Delta {C_D}$/10−4
    0.14 0 0 0 0 0 0 2.58 0.00795 0.0040 0
    −0.21 0.02 −1.11 −1.28 1.31 0.09 2.80 0.00787 0.0072 −0.8
    0.24 0 0 0 0 0 0 3.63 0.01148 −0.0049 0
    1.46 2.65 0.09 0.74 0.89 2.25 3.22 0.01095 −0.0157 −5.3
    下载: 导出CSV

    表  6  考虑配平约束时变弯度减阻优化结果

    Table  6.   Results of variable camber drag reduction optimization when considering pitch trim

    ${C_L}$ 舵 0/(°) 舵 1/(°) 舵 2/(°) 舵 3/(°) 舵 4/(°) 舵 5/(°) α/(°) ${C_D}$ ${C_M}$ $\Delta {C_D}$/10−4
    0.14 0 0 0 0 0 0 2.58 0.00795 0.0040 0
    4.91 0 0 0 0 0 2.41 0.00817 0.0003 2.2
    0.681 1.75 −0.501 −0.0914 0.422 1.65 2.45 0.00792 0.0004 −0.2
    0.24 0 0 0 0 0 0 3.63 0.01148 −0.0048 0
    −5.89 0 0 0 0 0 3.82 0.01228 −0.0001 8
    −1.18 −2.47 0.496 −0.423 −0.528 −0.186 3.83 0.01199 −0.0003 5.1
    下载: 导出CSV

    表  7  ${C_L} = 0.14$时主成分元素对应情况

    Table  7.   Principal component elements correspondence (${C_L} = 0.14$)

    主成分 舵 0/(°) 舵 1/(°) 舵 2/(°) 舵 3/(°) 舵 4/(°) 舵 5/(°)
    主成分1(93.73%) −0.426 −0.624 −0.172 −0.440 0.052 −0.451
    主成分2(4.25%) 0.679 −0.524 −0.067 0.112 0.494 0.057
    主成分3(1.05%) −0.199 −0.399 0.556 −0.161 −0.115 0.673
    主成分4(0.41%) −0.090 −0.267 −0.729 0.276 −0.370 0.420
    主成分5(0.32%) −0.101 0.323 −0.353 −0.574 0.517 0.405
    下载: 导出CSV

    表  8  ${C_{{L}}} = 0.24$时主成分元素对应情况

    Table  8.   Principal component elements correspondence (${C_{{L}}} = 0.14$)

    主成分 舵 0/(°) 舵 1/(°) 舵 2/(°) 舵 3/(°) 舵 4/(°) 舵 5/(°)
    主成分1(93.73%) −0.426 −0.624 −0.172 −0.440 0.052 −0.451
    主成分2(4.25%) 0.679 −0.524 −0.067 0.112 0.494 0.057
    主成分3(1.05%) −0.199 −0.399 0.556 −0.161 −0.115 0.673
    主成分4(0.41%) −0.090 −0.267 −0.729 0.276 −0.370 0.420
    主成分5(0.32%) −0.101 0.323 −0.353 −0.574 0.517 0.405
    下载: 导出CSV
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出版历程
  • 收稿日期:  2022-06-16
  • 录用日期:  2022-09-19
  • 网络出版日期:  2022-09-23
  • 整期出版日期:  2024-04-29

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