改进Kriging模型及在宽马赫数变几何进气道的应用

doi:10.3969/j.issn.1009-086x.2018.01.009

现代防御技术 ›› 2018, Vol. 46 ›› Issue (1): 56-62.DOI: 10.3969/j.issn.1009-086x.2018.01.009

改进Kriging模型及在宽马赫数变几何进气道的应用

徐珊珊¹, 金玉华², 张庆兵¹

1.北京电子工程总体研究所,北京 100854;
2.中国航天科工集团有限公司第二研究院,北京 100854

收稿日期:2017-09-30 修回日期:2017-10-25 出版日期:2018-02-28 发布日期:2020-11-25
作者简介:徐珊珊(1988-),女,湖北十堰人。博士生,主要从事飞行器设计研究。通信地址:100854 北京市142信箱30分箱 E-mail:hbxssok@126.com

Improved Kriging Model and Its Application in Variable Geometry Inlets with Large Mach Number

XU Shan-shan¹, JIN Yu-hua², ZHANG Qing-bing¹

1. Beijing Institute of Electronic System Engineering,Beijing 100854,China;
2. The Second Research Academy of CASIC,Beijing 100854,China

Received:2017-09-30 Revised:2017-10-25 Online:2018-02-28 Published:2020-11-25

摘要/Abstract

摘要： 由于参数多、计算量大,宽马赫数变几何进气道建模问题亟需精度足够高和计算速度足够快的代理模型。针对粒子群-Kriging代理模型优化步骤极易收敛到局部最优值的问题,采用带全局判据的改进量子粒子群优化方法加以代替。通过对测试函数的重构,验证该代理模型精确度。结果表明,该方法速度快,精度高,且对高度非线性函数的适应性强。针对Ma=2~4的二楔板反压式变几何进气道,构建了随马赫数、攻角、唇口水平位移、二级楔板角度和位置变化带来的流量系数和临界总压恢复系数的代理模型。结果表明,该算法适应度好、模型精度高,对该问题建模具有一定应用价值。

关键词: 变几何进气道, 宽马赫数, 代理模型方法, 流量系数, 总压恢复系数, 优化算法

Abstract: For multi-dimensional and huge amount calculations, an approximate model with sufficient accuracy and fast calculation speed for the variable geometry supersonic inlet with large Mach number range is needed urgently. To solve the convergence at partial-best point of current quantum-particle swarm optimization Kriging approximate model, the global criterion improved quantum-behaved particle swarm optimization is presented, which is validated with high precision, fast speed and strong adaption to high non-linear function by rebuilding two test functions. The approximate model of variable geometry supersonic inlets with 2~4 Mach number range is established by 5 variable parameters: Ma, angle of attack, horizontal displacement of cowl, second inlet ramp angle and its displacement. The application of the presented model method is validated with high accuracy and adaptability.

Key words: variable geometry inlet, large Mach number range, approximate model, flow coefficient captured by inlet, total recovery coefficient, optimization

中图分类号:

TJ760.3

徐珊珊, 金玉华, 张庆兵. 改进Kriging模型及在宽马赫数变几何进气道的应用[J]. 现代防御技术, 2018, 46(1): 56-62.

XU Shan-shan, JIN Yu-hua, ZHANG Qing-bing. Improved Kriging Model and Its Application in Variable Geometry Inlets with Large Mach Number[J]. Modern Defense Technology, 2018, 46(1): 56-62.

参考文献

[1] BOUCHEZ M,FALEMPIN F.Air breathing Space Launcher Interest of a Fully Variable Geometry Propulsion System Status 1999[R].AIAA-99-2376,1999.
[2] HUEBNER L D,ROCK K E,RUF E G,et al.Hyper-X Flight Engine Ground Testing for X-43 Flight Risk Reduction[R].AIAA-2001-1809,2001.
[3] FALEMPIN F,WENDLING E,GOLDFEILD M,et al.Experimental Investigation of Starting Process for a Variable Geometry Air Inlet Operating from Mach 2 to Mach 8[R].AIAA-2006-4513,2006.
[4] 卢燕,樊思齐,马会民.超声速进气道数学模型研究[J].推进技术,2002,23(6):468-471.
LU Yan,FAN Si-qi,MA Hui-min.Study for the Mathematical Model of Supersonic Inlet[J].Journal of Propulsion Technology,2002,23(6):468-471.
[5] 徐珊珊,金玉华,张庆兵,等.宽马赫数变几何进气道性能快速计算方[J].现代防御技术,2017,45(2):74-79+92.
XU Shan-shan,JIN Yu-hua,ZHANG Qing-bing,et al.A Mathematical Model for Fast Design of the Variable Geometry Supersonic Inlets with Large Mach Number Range[J].Modern Defence Technology,2017,45(2):74-79+92.
[6] KAYMAZ J.Application of Kriging Method to Structural Reliability Problems[J].Structural Safety,2005,27(2):133-151.
[7] DELLINO G,LINO P,MELONI C,et al.Kriging Metamodel Management in the Design Optimization of a CNC Injection System[J].Mathematics and Computers in Simulation,2009,29(10):2345-2360.
[8] 赵轲.基于CFD的复杂气动优化与稳健设计方法研究[D].西安:西北工业大学,2014.
ZHAO Ke.Complex Aerodynamic Optimization and Robust Design Method Based on Computational Fluid Dynamics[D].Xi’an:Northwestern Polytechnical University,2014.
[9] 吴先宇,罗世彬,陈小前.基于替代模型的高超声速进气道优化[J].弹箭与制导学报,2008,28(1):148-152.
WU Xiang-yu,LUO Shi-bin,CHEN Xiao-qian.Optimization of a Hypersonic Inlet Based on Surrogate Models.Journal of Projectiles,Rockets,Missiles and Guidance,2008,28(1):148-152.
[10] MARTIN J D,SIMPSON T W.Use of Kriging Models to Approximate Deterministic Computer Models[J].AIAA Journal,2005,43(4):854-863.
[11] 陈志英,任远,白广忱,等.粒子群优化的Kriging近似模型及其在可靠性分析中的应用[J].航空动力学报,2011,26(7):1522-1530.
CHEN Zhi-ying,REN Yuan,BAI Guang-chen,et al.Particle Swarm Optimized Kriging Approximate Model and its Application to Reliability Analysis[J].Journal of Aerospace Power,2011,26(7):1522-1530.
[12] SUN Jun,XU Wen-bo,FENG Bin.A Global Search Strategy of Quantum-Behaved Particle Swarm Optimization[C]//Proceedings of the IEEE Congress on Cybernetics and Intelligent System,Singapore:IEEE Press,2004:111-116.
[13] 黄泽霞,俞攸红,黄德才,等.惯性权自适应调整的量子粒子群优化算法[J].上海交通大学学报,2012,46(2):228-232.
HUANG Ze-xia,YU You-hong,HUANG De-cai,Quantum-behaved Particle Swarm Alogorithm with Self-Adapting Adjustment of Inertia Weight[J].Journal of Shanghai Jiaotong University,2012,46(2):228-232.
[14] XIA Chen-chao,JIANG Ting-ting,CHEN Wei-fang.Particle Swarm Optimization of Aerodynamic Shapes with Nonuniform Shape Parameter-Based Radial Basis Function[J].Journal of Aerospace Engineering,2017,30(3):04016089 1-12.
[15] 蔡飞超,陈凤明,徐东来,等.宽Ma数范围固定几何进气道设计问题研究[J].固体火箭技术,2010,33(2):163-166.
CAI Fei-chao,CHEN Feng-ming,XU Dong-lai,et al.Study on Fixed-Geometry Supersonic Inlet Design for Wide Mach Number Range Application[J].Journal of Solid Rocket Technology,2010,33(2):163-166.

改进Kriging模型及在宽马赫数变几何进气道的应用

Improved Kriging Model and Its Application in Variable Geometry Inlets with Large Mach Number

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