A reduced order aerothermodynamic modeling framework for hypersonic vehicles based on surrogate and POD

被引:0
|
作者
Chen Xin [1 ]
Liu Li [2 ]
Long Teng [1 ]
Yue Zhenjiang [1 ]
机构
[1] School of Aerospace Engineering, Beijing Institute of Technology
[2] Key Laboratory of Dynamics and Control of Flight Vehicle, Ministry of Education, Beijing Institute of Technology
基金
中国国家自然科学基金;
关键词
Hypersonic vehicles; Aerothermodynamic; Reduced order model(ROM); Surrogate; Proper orthogonal decomposition(POD);
D O I
暂无
中图分类号
V211 [空气动力学];
学科分类号
0801 ; 080103 ; 080104 ;
摘要
Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient computation of the aerothermodynamics is one of the primary challenges for hypersonic aerothermoelastic analysis. Aimed at solving the shortcomings of engineering calculation, computation fluid dynamics(CFD) and experimental investigation, a reduced order modeling(ROM)framework for aerothermodynamics based on CFD predictions using an enhanced algorithm of fast maximin Latin hypercube design is developed. Both proper orthogonal decomposition(POD) and surrogate are considered and compared to construct ROMs. Two surrogate approaches named Kriging and optimized radial basis function(ORBF) are utilized to construct ROMs. Furthermore,an enhanced algorithm of fast maximin Latin hypercube design is proposed, which proves to be helpful to improve the precisions of ROMs. Test results for the three-dimensional aerothermodynamic over a hypersonic surface indicate that: the ROMs precision based on Kriging is better than that by ORBF, ROMs based on Kriging are marginally more accurate than ROMs based on PODKriging. In a word, the ROM framework for hypersonic aerothermodynamics has good precision and efficiency.
引用
收藏
页码:1328 / 1342
页数:15
相关论文
共 50 条
  • [1] A reduced order aerothermodynamic modeling framework for hypersonic vehicles based on surrogate and POD
    Chen Xin
    Liu Li
    Long Teng
    Yue Zhenjiang
    CHINESE JOURNAL OF AERONAUTICS, 2015, 28 (05) : 1328 - 1342
  • [2] Reduced order aerothermodynamic modeling research for hypersonic vehicles based on proper orthogonal decomposition and surrogate method
    Chen, Xin
    Liu, Li
    Yue, Zhenjiang
    Hangkong Xuebao/Acta Aeronautica et Astronautica Sinica, 2015, 36 (02): : 462 - 472
  • [3] Adding-Point Strategy for Surrogate-Based Reduced-Order Hypersonic Aerothermodynamic Modeling Based on Fuzzy Clustering
    Chen, Xin
    Cao, Zhanwei
    Fu, Bin
    Xu, Xiaoliang
    Yan, Hao
    Wang, Peixiao
    Zhang, Hanyi
    JOURNAL OF SPACECRAFT AND ROCKETS, 2021, 58 (01) : 244 - 253
  • [4] An aerothermodynamic design optimization framework for hypersonic vehicles
    Di Giorgio, Simone
    Quagliarella, Domenico
    Pezzella, Giuseppe
    Pirozzoli, Sergio
    AEROSPACE SCIENCE AND TECHNOLOGY, 2019, 84 : 339 - 347
  • [5] Nonlinear Thermal Reduced-Order Modeling for Hypersonic Vehicles
    Klock, Ryan J.
    Cesnik, Carlos E. S.
    AIAA JOURNAL, 2017, 55 (07) : 2358 - 2368
  • [6] Model reduction of aerothermodynamic for hypersonic aerothermoelasticity based on POD and Chebyshev method
    Yan Xiaoxuan
    Han Jinglong
    Zhang Bing
    Yuan Haiwei
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING, 2019, 233 (10) : 3734 - 3748
  • [7] Parametric reduced-order modeling of unsteady aerodynamics for hypersonic vehicles
    Chen, Zhiqiang
    Zhao, Yonghui
    Huang, Rui
    AEROSPACE SCIENCE AND TECHNOLOGY, 2019, 87 : 1 - 14
  • [8] Reduced-Order Nonlinear Unsteady Aerodynamic Modeling Using a Surrogate-Based Recurrence Framework
    Glaz, Bryan
    Liu, Li
    Friedmann, Peretz P.
    AIAA JOURNAL, 2010, 48 (10) : 2418 - 2429
  • [9] Surrogate-Based Multi-Objective Aerothermodynamic Design Optimization of Hypersonic Spiked Bodies
    Ahmed, M. Y. M.
    Qin, N.
    AIAA JOURNAL, 2012, 50 (04) : 797 - 810
  • [10] Principal interval decomposition framework for POD reduced-order modeling of convective Boussinesq flows
    San, O.
    Borggaard, J.
    INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN FLUIDS, 2015, 78 (01) : 37 - 62