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ACTA AERONAUTICAET ASTRONAUTICA SINICA ›› 2015, Vol. 36 ›› Issue (2): 462-472.doi: 10.7527/S1000-6893.2014.0079

• Fluid Mechanics and Flight Mechanics • Previous Articles     Next Articles

Reduced order aerothermodynamic modeling research for hypersonic vehicles based on proper orthogonal decomposition and surrogate method

CHEN Xin1,2, LIU Li1,2, YUE Zhenjiang1,2   

  1. 1. School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China;
    2. Key Laboratory of Dynamics and Control of Flight Vehicle, Ministry of Education, Beijing Institute of Technology, Beijing 100081, China
  • Received:2014-03-12 Revised:2014-04-24 Online:2015-02-15 Published:2014-05-15
  • Supported by:

    National Natural Science Foundation of China (11372036)

Abstract:

Aerothermoelasticity is one of the key technologies for hypersonic vehicles. Accurate and efficient estimation of aerodynamic heating is the basis of the aerothermoelasticity. Aimed at solving the shortcomings of engineering calculation and computational fluid dynamics, a novel estimation method based on proper orthogonal decomposition (POD) and surrogate(POD-Surrogate) method is proposed. Furthermore, a reduced order modeling framework for aerothermodynamic is developed. Test results for the three-dimensional aerothermodynamic over a hypersonic control surface indicate that the average L errors for POD-Kriging method and POD-RBF (Radial Basis Function) method can reach 6% and 14%, and the average normalized root mean square error (NRMSE) errors can reach 4% and 12%. Using more POD basis modes would not obviously improve the estimation precision when the basis modes reach 20. Reduced order models for the three-dimensional aerothermodynamics over a hypersonic control surface indicate that the precision of POD-Kriging method is better than that of POD-RBF method. In a word, the reduced order modeling for three-dimensional aerothermodynamics has good precision and efficiency.

Key words: hypersonic, aerothermodynamic, proper orthogonal decomposition, surrogate model, reduced order model

CLC Number: