基于FFD技术的大型运输机上翘后体气动优化设计

doi:10.7527/S1000-6893.2013.0315

流体力学与飞行力学

本期目录 | 过刊浏览 | 高级检索

前一篇 | 后一篇

基于FFD技术的大型运输机上翘后体气动优化设计

王元元^1,2, 张彬乾¹, 郭兆电³, 董强³

1. 西北工业大学翼型叶栅空气动力国家重点实验室, 陕西西安 710072;
2. 中国航空工业发展研究中心, 北京 100012;
3. 中航工业第一飞机设计研究院, 陕西西安 710089

收稿日期:2012-09-25 修回日期:2012-12-02 出版日期:2013-08-25 发布日期:2012-12-18
通讯作者: 张彬乾 E-mail:bqzhang@nwpu.edu.cn
作者简介:王元元男,博士研究生。主要研究方向:飞行器气动布局设计,航空情报研究。E-mail:wyy_7758521@hotmail.com;张彬乾男,教授,博士生导师。主要研究方向:飞行器设计,实验流体力学。Tel:029-88494846 E-mail:bqzhang@nwpu.edu.cn

Aerodynamic Optimization Design for Large Upswept Afterbody of Transport Aircraft Based on FFD Technology

WANG Yuanyuan^1,2, ZHANG Binqian¹, GUO Zhaodian³, DONG Qiang³

1. National Key Laboratory of Aerodynamic Design and Research, Northwestern Polytechnical University, Xi'an 710072, China;
2. Aviation Industry Development Research Centre of China, Beijing 100012, China;
3. The First Aircraft Institute of AVIC, Xi'an 710089, China

Received:2012-09-25 Revised:2012-12-02 Online:2013-08-25 Published:2012-12-18

摘要/Abstract

摘要：

利用非均匀有理B样条(NURBS)基函数属性建立了任意空间的自由变形(FFD)参数化方法,进一步结合无限插值(TFI)变形网格技术、二阶振荡粒子群优化(PSO)算法以及计算流体力学(CFD)数值模拟技术,构建了通用的气动外形优化设计系统。采用该系统对C17运输机上翘后体进行气动优化设计,在满足后体最大宽度、高度以及上翘角不减小的情况下,巡航状态减阻2.6%,压差阻力减小19.8%。流态分析显示,优化后体阻力减小的主要原因是后体截面近圆度的增加以及近圆度沿机身轴线的变化量的减小使得后体周向逆压梯度减小所致。研究结果表明本文建立的基于FFD技术的气动优化设计系统对于大型运输机上翘后体的气动优化设计具有较好的实用性。

关键词: FFD技术, 非均匀有理B样条, 粒子群优化算法, 计算流体力学, 大型运输机, 上翘后体, 气动优化设计

Abstract:

A free-form deformation parameterization (FFD) method is established based on non-uniform rational B-spline (NURBS) basis function. Furthermore, by coupling the transfinite interpolation (TFI) grid deformation technology and computational fluid dynamics (CFD) method with improved particle swarm optimization (PSO) arithmetic,a general aerodynamic optimization design system is constructed. Then, the aerodynamic optimization design system is applied to designing a large upswept afterbody of transport aircraft C17 on the restrictions of nondecreasing maximum structure height, width and upswept angle. The optimized afterbody decreases the total drag by 2.6% and pressure drag by 19.8% respectively. A comparison analysis of the aerodynamic shape and flow pattern reveals that the key factors for the optimized afterbody to decrease the pressure drag greatly are the increased near-roundness of the afterbody cross-section and decreased near-roundness change ratio along the fuselage axis. The two factors enable the adverse pressure gradient along the circumferential direction to become smaller, which can suspend aferbody separation and weaken afterbody vortex strength. The aerodynamic optimization design system constructed in this paper has good practicability and engineering application prospect.

Key words: FFD technique, non-uniform rational B-spline, particle swarm optimization, computational fluid dynamics, large transport aircraft, upswept aferbody, aerodynamic optimization design

中图分类号:

V211.42

王元元, 张彬乾, 郭兆电, 董强. 基于FFD技术的大型运输机上翘后体气动优化设计[J]. 航空学报, 2013, 34(8): 1806-1814.

WANG Yuanyuan, ZHANG Binqian, GUO Zhaodian, DONG Qiang. Aerodynamic Optimization Design for Large Upswept Afterbody of Transport Aircraft Based on FFD Technology[J]. ACTA AERONAUTICAET ASTRONAUTICA SINICA, 2013, 34(8): 1806-1814.

参考文献

[1] Yu Y Z, Liu J F, Jiang Z, et al. The investigation of flow control and drag reduction mechanism for thansport airplane aft-body. Acta Aerodynamica Sinica, 2011, 29(5): 640-644.(in Chinese) 于彦泽, 刘景飞, 蒋增, 等.大型飞机后体流动控制及减阻机理研究. 空气动力学学报, 2011, 29(5): 640-644.
[2] Zhang B Q, Wang Y Y, Duan Z Y, et al. Design method for large upswept afterbody of transport aircraft. Acta Aeronautica et Astronautica Sinica, 2010, 31(10): 1933-1939.(in Chinese) 张彬乾, 王元元, 段卓毅, 等.大上翘机身后体设计方法. 航空学报, 2010, 31(10): 1933-1939.
[3] Sederberg T W, Parry S R. Freeform deformation of solid geometric models. Computer Graphics, 1986, 22(4): 151-160.
[4] Coquilart S. Extended free-form deformations: a sculpturing tool for 3D geometric modeling. Computer Graphics,1990, 24(4): 187-196.
[5] Hsu W M, Hughes J F, Kaufman H. Direct manipulation of free-form deformation. Computer Graphics, 1992, 26(2): 177-184.
[6] Zhu X X. Modeling technology of free-form curve and surface. Beijing: Science Press, 2000: 70-85.(in Chinese) 朱心雄. 自由曲线曲面造型技术. 北京:科学出版社, 2000: 70-85.
[7] Kalra P, Mangili A, Thalmann N M, et al. Simulation of facial muscle actions based on rational free form deformation. Computer Graphics, 1992, 2(3): 59-69.
[8] Lamousin H J, Waggenspack W N. NURBS-based free-form deformations. Computer Graphics and Applications, 1994, 14(6): 59-65.
[9] Mengistu T T, Ghaly W S. A geometric representation of turbomachinery cascades using NURBS. AIAA-2002-318, 2002.
[10] Xing X Q, Damodaran M. Design of three-dimensional nozzle shape using NURBS, CFD and hybrid optimization strategies. AIAA-2004-4368, 2004.
[11] Dubuc L, Cantariti F, Woodgate M, et al. A grid deformation technique for unsteady flow computations. International Journal for Numerical Methods in Fluids, 2002, 32(3): 285-311.
[12] Smith R E. Transfinite interpolation (TFI) generation systems. In: Handbook of Grid Generation. England: CRC Press, 1998: 5-38.
[13] Wang Y Y, Zhang B Q, Chen Y C. Robust airfoil optimization based on improved particle swarm optimization method. Applied Mathematics and Mechanics, 2011, 32(10): 1245-1254.
[14] Patnaik S N. Neural network and regression approximations in high speed civil transport aircraft design optimization. NASA/TM-1998-206316, 1998.
[15] McKay M D, Beckman R J. A comparison of three methods for selecting values of input variables in the analysis of output from a computer code. Technometrics (American Statistical Association), 1979, 21(2): 239-245.

E-mail：hkxb@buaa.edu.cn

关于我们

期刊社服务

专业学科

封面文章

友情链接

主管单位：中国科学技术协会主办单位：中国航空学会北京航空航天大学

基于FFD技术的大型运输机上翘后体气动优化设计

Aerodynamic Optimization Design for Large Upswept Afterbody of Transport Aircraft Based on FFD Technology

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	乔建领, 韩忠华, 丁玉临, 宋文萍, 宋笔锋. 分层大气湍流场对远场声爆传播的影响[J]. 航空学报, 2023, 44(2): 626350-626350.
[2]	罗佳杰, 宋文滨. 层流机翼及其增升装置嵌套协同优化方法[J]. 航空学报, 2022, 43(8): 125377-125377.
[3]	夏侯唐凡, 陈江涛, 邵志栋, 吴晓军, 刘宇. 随机和认知不确定性框架下的CFD模型确认度量综述[J]. 航空学报, 2022, 43(8): 25716-025716.
[4]	陈广强, 豆国辉, 魏昊功, 邹昕, 李齐, 刘周, 周伟江. 火星探测器大气数据测量方法[J]. 航空学报, 2022, 43(3): 626619-626619.
[5]	奕建苗, 邓枫, 覃宁, 刘学强. 快速预测跨声速流场的深度学习方法[J]. 航空学报, 2022, 43(11): 526747-526747.
[6]	杨体浩, 白俊强, 段卓毅, 史亚云, 邓一菊, 周铸. 喷气式客机层流翼气动设计综述[J]. 航空学报, 2022, 43(11): 527016-527016.
[7]	王迪, 钱战森, 冷岩. 广义Burgers方程声爆传播模型高阶格式离散[J]. 航空学报, 2022, 43(1): 124916-124916.
[8]	鲍俊, 王瑜, 牛潜, 朱锡冬, 程建杰. 喷雾液滴撞击液膜影响参数及流动机理分析[J]. 航空学报, 2021, 42(S1): 726360-726360.
[9]	王子航, 吕宏强. 基于CFD高精度算法的雷电电磁场研究[J]. 航空学报, 2021, 42(S1): 726366-726366.
[10]	陈坚强, 吴晓军, 张健, 李彬, 贾洪印, 周乃春. FlowStar:国家数值风洞(NNW)工程非结构通用CFD软件[J]. 航空学报, 2021, 42(9): 625739-625739.
[11]	李左飙, 温风波, 唐晓雷, 苏良俊, 王松涛. 基于深度学习的单排孔气膜冷却性能预测[J]. 航空学报, 2021, 42(4): 524331-524331.
[12]	杨肖峰, 李芹, 杜雁霞, 刘磊, 桂业伟. 高超声速飞行器界面多相催化数值研究进展[J]. 航空学报, 2021, 42(12): 625908-625908.
[13]	常思源, 白晓征, 刘君. 一种基于聚类分析的二维激波模式识别算法[J]. 航空学报, 2020, 41(8): 123626-123626.
[14]	刘峰博, 蒋城, 马涂亮, 梁益华. 伴随压力分布反设计方法在大型客机气动优化中的初步探索[J]. 航空学报, 2020, 41(5): 623372-623372.
[15]	韩忠华, 许晨舟, 乔建领, 柳斐, 池江波, 孟冠宇, 张科施, 宋文萍. 基于代理模型的高效全局气动优化设计方法研究进展[J]. 航空学报, 2020, 41(5): 623344-623344.