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复合式无人机机翼设计及其自适应优化

张威 谭蒙 刘亚枫 聂永斌 栾悦

张威, 谭蒙, 刘亚枫, 聂永斌, 栾悦. 复合式无人机机翼设计及其自适应优化[J]. 气体物理, 2024, 9(2): 54-65. doi: 10.19527/j.cnki.2096-1642.1091
引用本文: 张威, 谭蒙, 刘亚枫, 聂永斌, 栾悦. 复合式无人机机翼设计及其自适应优化[J]. 气体物理, 2024, 9(2): 54-65. doi: 10.19527/j.cnki.2096-1642.1091
ZHANG Wei, TAN Meng, LIU Yafeng, NIE Yongbin, LUAN Yue. Wing Design and Adaptive Optimization of a Compound Drone[J]. PHYSICS OF GASES, 2024, 9(2): 54-65. doi: 10.19527/j.cnki.2096-1642.1091
Citation: ZHANG Wei, TAN Meng, LIU Yafeng, NIE Yongbin, LUAN Yue. Wing Design and Adaptive Optimization of a Compound Drone[J]. PHYSICS OF GASES, 2024, 9(2): 54-65. doi: 10.19527/j.cnki.2096-1642.1091

复合式无人机机翼设计及其自适应优化

doi: 10.19527/j.cnki.2096-1642.1091
详细信息
    作者简介:

    张威(1994—)男, 博士, 主要研究方向为气动设计、气动优化等。E-mail: optz2023@163.com

    通讯作者:

    栾悦(1994-)女, 工程师, 主要研究方向为数据分析、统计分析等。E-mail: optl2022@163.com

  • 中图分类号: V211.3

Wing Design and Adaptive Optimization of a Compound Drone

  • 摘要: 随着人类社会的进步和城市物流的兴起, 以复合式无人机为代表的无人机技术进入了快速发展阶段。在复合式无人机的研制周期中, 气动优化设计选型扮演着非常重要的角色。针对基于代理模型的气动优化技术, 对其关键参数自适应筛选和设计空间自适应更新进行了研究, 形成了参数/空间自适应气动寻优平台, 有效提高了气动优化过程中的寻优效率和搜索能力。针对一款复合式无人机提出机翼初步设计方案, 并对其进行自适应气动寻优。优化翼根、翼梢翼型及由此生成的优化三维机翼在设计升力系数为1.0时的升阻比均提高5%以上, 且对应迎角均减小2°以上。无人机机翼失速特性及滚转操控能力均得到有效提升。

     

  • 图  1  一款复合式无人机概念外形

    Figure  1.  Conceptual shape of a compound drone

    图  2  自适应气动寻优算法流程图

    Figure  2.  Flow chart of parametric/spatial adaptive aerodynamic optimization algorithm

    图  3  NACA4412翼型计算网格示意图

    Figure  3.  Computational mesh diagram of NACA4412 airfoil

    图  4  网格无关性验证结果

    Figure  4.  Verification result of mesh independence

    图  5  翼根翼型优化迭代历程

    Figure  5.  Iteration of wing root airfoil optimization

    图  6  优化前后翼型形状及压力系数分布对比

    Figure  6.  Comparisons of shape and surface pressure coefficient between airfoils before and after optimization

    图  7  优化前后翼型性能对比

    Figure  7.  Performance comparison between airfoils before and after optimization

    图  8  优化前后机翼性能对比

    Figure  8.  Performance comparison between wings before and after optimization

    图  9  优化前后机翼上翼面极限流线分布(上:初始机翼;下:优化机翼)

    Figure  9.  Limiting streamline distribution on upper surface of wings before and after optimization (upper: original wing; lower: optimized wing)

    表  1  无人机设计参数

    Table  1.   Conceptual design parameters of a drone

    design parameter value
    maximum take-off weight/kg 500
    wing area/m2 7.5
    cruising altitude/m 1 000
    cruising speed/(km/h) 130
    下载: 导出CSV

    表  2  无人机机翼设计参数

    Table  2.   Wing geometry design parameters of a drone

    design parameter value
    wing area/m2 7.5
    wing span/m 10
    aspect ratio 13.33
    taper ratio 0.5
    mean aerodynamic chord/m 0.777
    angle of sweepback at trailing edge/(°) 0
    dihedral angle/(°) 0
    下载: 导出CSV

    表  3  方差分析表

    Table  3.   Variance analysis

    source S df MS F value P value
    A SA dfA MSA FA PA
    B SB dfB MSB FB PB
    error SE dfE MSE
    total ST dfT
    下载: 导出CSV

    表  4  参数空间更新伪代码

    Table  4.   Pseudo-code of parameter space updating

    Input: original parameter space[xil, old, xiu, old]k,temporary optimal points(x1, opt, x2, opt, …, xk, opt)
    Process:
    1. For i=1, 2, …, k Do:
    2.   If xi, opt -xil, old ≤ 0.1|xiu, old-xil, old | Then
    3.     xil, new=(3xil, oldxiu, old)/2, xiu, new=(xil, old+ xiu, old)/2;
    4.   Else if xiu, old-xi, opt≤ 0.1|xiu, old-xil, old | Then
    5.     xil, new=(xil, old+ xiu, old)/2, xiu, new=(-xil, old+3xiu, old)/2;
    6.   Else
    7.     xil, new=xil, old, xiu, new=xiu, old;
    8.   End if
    9. End for
    Output: new parameter space[xil, new-xiu, new]k
    下载: 导出CSV

    表  5  网格无关性验证参数

    Table  5.   Parameters of mesh independence verification

    mesh parameter coarse mesh middle mesh dense mesh
    chord point number 81 121 161
    y+ 5.0 1.0 0.5
    total mesh number 24 764 36 844 48 924
    下载: 导出CSV

    表  6  计算工况

    Table  6.   Calculation conditions

    H/m V/(km/h)
    1 000 130
    下载: 导出CSV

    表  7  翼根翼型设计升阻比的方差分析表

    Table  7.   Variance analysis of design lift-to-drag ratio of root airfoil

    source S df MS F value P value
    U1, root 14.19 1 14.19 152.00 25.77
    U2, root 17.88 1 17.88 191.56 32.47
    U3, root 0.95 1 0.95 10.20 1.73
    U4, root 0.06 1 0.06 0.62 0.11
    U5, root 0.00 1 0.00 0.01 0.00
    U6, root 1.03 1 1.03 11.02 1.87
    U7, root 1.01 1 1.01 10.81 1.83
    L1, root 2.22 1 2.22 23.80 4.03
    L2, root 0.73 1 0.73 7.82 1.33
    L3, root 6.95 1 6.95 74.49 12.62
    L4, root 0.16 1 0.16 1.74 0.29
    L5, root 5.86 1 5.86 62.74 10.64
    L6, root 0.48 1 0.48 5.13 0.87
    L7, root 1.96 1 1.96 21.03 3.56
    error 1.59 17 0.09 2.89
    total 55.07 31 100.00
    下载: 导出CSV

    表  8  关键参数筛选结果

    Table  8.   Screening results of key parameters

    root design parameters tip design parameters
    U1, root U2, root U3, root U4, root U1, tip U2, tip U3, tip U4, tip
    U5, root U6, root U7, root U5, tip U6, tip U7, tip
    L1, root L2, root L3, root L4, root L1, tip L2, tip L3, tip L4, tip
    L5, root L6, root L7, root L5, tip L6, tip L7, tip
    下载: 导出CSV

    表  9  翼根翼型参数空间变化情况

    Table  9.   Parameter space variation of wing root airfoil

    parameter original space latest space optimal
    lower upper lower upper
    L1, root -0.26 -0.2 -0.14 -0.08 -0.091
    L3, root -3.9 -2.9 -1.9 -0.9 -1.404 4
    L5, root -3.9 -2.9 -0.9 0.1 -0.001 2
    L7, root 0.1 0.13 0.16 0.19 0.184
    U1, root 0.23 0.31 0.19 0.27 0.193 6
    U2, root 1.8 2.4 1.8 2.4 2.17
    U3, root 2.3 3.1 3.5 4.3 4.27
    U4, root 5.9 7.9 5.9 7.9 6.03
    U6, root 1.4 1.8 3.0 3.4 3.13
    下载: 导出CSV

    表  10  优化翼型气动性能变化情况

    Table  10.   Aerodynamic performance variation of optimal airfoils

    aerodynamic performance original optimal variation
    root airfoils KCL=1, root 64.83 70.11 +8.14%
    αCL=1, root 5.38° 3.12° -2.26°
    αstall, root 14.5° 14.5° +0.0°
    θstall 0.159 8 0.140 4 -0.019 4
    tip airfoils KCL=1, tip 62.61 67.17 +7.28%
    αCL=1, tip 4.83° 1.93° -2.90°
    αstall, tip 14.5° 13.0° -1.5°
    θtip 0.122 0 0.109 9 -0.012 1
    下载: 导出CSV
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  • 收稿日期:  2023-10-22
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