基于降阶模型的翼型结冰冰形预测方法

doi:10.13700/j.bh.1001-5965.2018.0474

北京航空航天大学学报 ›› 2019, Vol. 45 ›› Issue (5): 1033-1041.doi: 10.13700/j.bh.1001-5965.2018.0474

基于降阶模型的翼型结冰冰形预测方法

刘藤, 李栋, 黄冉冉, 张振辉

西北工业大学航空学院, 西安 710072

收稿日期:2018-08-14 出版日期:2019-05-20 发布日期:2019-05-21
通讯作者: 李栋.E-mail:ldgh@nwpu.edu.cn E-mail:ldgh@nwpu.edu.cn
作者简介:刘藤男,硕士研究生。主要研究方向:计算流体力学;李栋男,博士,教授,博士生导师。主要研究方向:设计空气动力学、计算流体力学。

Ice shape prediction method of aero-icing based on reduced order model

LIU Teng, LI Dong, HUANG Ranran, ZHANG Zhenhui

School of Aeronautics, Northwestern Polytechnical University, Xi'an 710072, China

Received:2018-08-14 Online:2019-05-20 Published:2019-05-21

摘要/Abstract

摘要： 翼型结冰冰形的数值模拟预测通常比较复杂耗时，为了更加快速准确地预测冰形以减少计算资源消耗，建立了基于本征正交分解（POD）和Kriging模型的冰形快速预测方法。利用CFD数值模拟结果来构建样本空间，以飞行迎角为例详述了降阶模型的冰形预测的实现手段，并结合试验设计方法，完成了多参数的结冰冰形快速预测，同时研究了先进的Blind-Kriging模型的相关方法以及对于预测结果的改进。结果表明，降阶模型预测翼型结冰冰形与CFD数值模拟结果吻合较好，表明降阶模型可以快速、精确地应用于翼型结冰冰形预测。

关键词: 冰形预测, 降阶模型, 本征正交分解(POD), Kriging模型, Blind-Kriging模型

Abstract: The numerical simulation prediction of aero-icing ice shape is usually complicated and time-consuming. In order to predict ice shape more quickly and accurately and to reduce computational resource consumption, a quick ice shape prediction method based on proper orthogonal decomposition and Kriging model is proposed in this paper. Using a database of high-fidelity CFD numerical simulations to build sample space, in view of the change of attack angle, the procedure for predicting the ice shape by reduced order model is introduced. With the data sampling method of parameter space, multiparameter prediction of the ice shape is achieved. Meanwhile, the related methods of the advanced Blind-Kriging model and the improvement of the prediction results are studied. The result shows that the prediction results of the airfoil icing shape using the reduced order model agree well with the CFD numerical simulation results. The conclusion is made that the reduced order model is a quick and accurate approach for predicting the ice shapes of airfoil icing.

Key words: ice-shape prediction, reduced order model, proper orthogonal decomposition (POD), Kriging model, Blind-Kriging model

中图分类号:

V211⁺.3

刘藤, 李栋, 黄冉冉, 张振辉. 基于降阶模型的翼型结冰冰形预测方法[J]. 北京航空航天大学学报, 2019, 45(5): 1033-1041.

LIU Teng, LI Dong, HUANG Ranran, ZHANG Zhenhui. Ice shape prediction method of aero-icing based on reduced order model[J]. JOURNAL OF BEIJING UNIVERSITY OF AERONAUTICS AND A, 2019, 45(5): 1033-1041.

参考文献

[1] 蒋天俊.结冰对飞机飞行性能影响的研究[D]. 南京:南京航空航天大学,2008.JIANG T J.Investigation of icing accretion influences on aircraft flight performance[D]. Nanjing:Nanjing University of Aeronautics and Astronautics,2008(in Chinese).
[2] 姚若鹏.翼型的结冰数值模拟及相关控制研究[D].南京:南京航空航天大学,2012.YAO R P.The numerical simulation of ice accretion on airfoil and control research[D].Nanjing:Nanjing University of Aeronautics and Astronautics,2012(in Chinese).
[3] 杨胜华.二维飞机结冰过程仿真[D].北京:北京航空航天大学,2010.YANG S H.Two-dimensional in-flight ice accretion simulation[D].Beijing:Beihang University,2010(in Chinese).
[4] 申晓斌,郁嘉,林贵平,等.基于特征正交分解法的翼型结冰冰形快速预测[J].航空动力学报,2013,28(4):807-812.SHEN X B,YU J,LIN G P,et al.Fast prediction of ice shape based on proper orthogonal decomposition method[J].Journal of Aerospace Power,2013,28(4):807-812(in Chinese).
[5] GALLIVAN K,GRIMME E,VAN DOOREN P.Pade approximation of large-scale dynamics systems with lanczos methods[C]//Proceedings of the 33rd IEEE Conference on Decision and Control.Piscataway,NJ:IEEE Press,1994:443-448.
[6] CAMUSSI R,GUJ G.Orthonormal wavelet decomposition of turbulent flows:Intermittency and coherent structures[J].Journal of Fluid Mechanics,1997,348:177-199.
[7] AUBRY N,GUYONNET R,LIMA R.Spatio-temporal analysis of complex signals:Theory and applications[J].Journal of Statistical Physics,1981,64(3-4):683-739.
[8] HOLMES P,LUMLEY J L,BERKOOZ G.Turbulence,coherent structures,dynamical systems and symmetry[M].Cambridge:Cambridge University Press,1996:68-100.
[9] VOLKWEIN S.Proper orthogonal decomposition for nonlinear dynamical systems[EB/OL].Graz:University of Graz,2005[2018-08-14] http://www.math.unikonstanz.de/numerik/personen/volkwein/PhDSchools/Volkwein_Part1.pdf.
[10] NAKAKITA K,HABASHI W G,NADARAJAH S.Toward real-time aero-icing simulation using reduced order models[J].Journal of Aircraft,2010,47(1):96-115.
[11] 葛宜元.试验设计方法与Design-Expert软件应用[M].哈尔滨:哈尔滨工业大学出版社,2015:2-3.GE Y Y.Experimental design method and Design-Expert software application[M].Harbin:Harbin Institute of Technology Press,2015:2-3(in Chinese).
[12] MCKAY M D,BECKMAN R J,CONOVER W J.A comparison of three methods for selecting values of input variables in the analysis of output from a computer code[J].Technometrics,1979,21(2):239-245.
[13] MORRIS M D,MITCHELL T J.Exploratory designs for computational experiments[J].Journal of Statistical Planning and Inference,1995,43(3):381-402.
[14] 丁鹏,陶文诠.建立低阶模型的POD方法[J].工程热物理学报,2009,30(6):1019-1021.DING P,TAO W Q.Reduced order modeling with the proper orthogonal decomposition[J].Journal of Engineering Thermo Physics,2009,30(6):1019-1021(in Chinese).
[15] KERSCHEN G,GOLINVAL J,VAKAKIS A F,et al.The method of proper orthogonal de-composition for dynamical characterization and order reduction of mechanical sys-tems:An overview[J].Nonlinear Dynamics,2005,41(1-3):147-169.
[16] SIROVICH L.Turbulence and the dynamics of coherent structures.Ⅰ-Coherent structures.Ⅱ-Symmetries and transformations.Ⅲ-Dynamics and scaling[J].Quarterly of Applied Mathematics,1987,45(3):561-571.
[17] KRIGE D G.A statistical approach to some basic mine valuation problems on the Witwatersrand[J].Journal of the Southern African Institute of Mining and Metallurgy,1951,52(6):119-139.
[18] 韩忠华.Kriging模型及代理优化算法研究进展[J].航空学报,2016,37(11):3197-3225.HAN Z H.Kriging surrogate model and its application to design optimization:A review of recent progress[J].Acta Aeronautica et Astronautica Sinica,2016,37(11):3197-3225(in Chinese).
[19] HÉLOÏSE B,FRANÇOIS M,WAGDI G H.FENSAP-ICE's three-dimensional in-flight ice accretion module:ICE3D[J].Journal of Aircraft,2003,40(2):239-247.
[20] JEONG S,OBAYASHI S,YAMAMOTO K.Aerodynamic optimization design with kriging model[J].Transactions of the Japan Society for Aeronautical and Space Sciences,2005,48(161):161-168.
[21] JECK R K.Icing Design Envelopes(14 CFR Parts 25 and 29,Appenddix C)Converted to a Distance-Based Format:DOT/FAA/AR-00/30[R].Washington,D.C.:FAA,2002.
[22] JOSEPH V R,HUNG Y,SUDJANTO A.Blind Kriging:A new method for developing metamodels[J].Journal of Mechanical Design,2008,130(3):350-353.
[23] COUCKUYT I,FORRESTER A,GORISSEN D,et al.Blind Kriging:Implementation and performance analysis[J].Advances in Engineering Software,2012,49:1-13.

基于降阶模型的翼型结冰冰形预测方法

Ice shape prediction method of aero-icing based on reduced order model

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 4

编辑推荐

Metrics

本文评价

[1]	李魁, 邓小龙, 杨希祥, 侯中喜. 基于平流层风场预测的浮空器轨迹控制[J]. 北京航空航天大学学报, 2019, 45(5): 1008-1018.
[2]	魏娟, 张建国, 邱涛. 基于改进的动态Kriging模型的结构可靠度算法[J]. 北京航空航天大学学报, 2019, 45(2): 373-380.
[3]	宋鑫, 郑冠男, 杨国伟, 姜倩. 几何不确定性区间分析及鲁棒气动优化设计[J]. 北京航空航天大学学报, 2019, 45(11): 2217-2227.
[4]	林康, 马云鹏, 武哲, 王强. 基于Kriging模型的浮空器氦气昼夜温差最优化[J]. 北京航空航天大学学报, 2018, 44(3): 542-548.