Journal of Astronautics ›› 2020, Vol. 41 ›› Issue (9): 1141-1150.doi: 10.3873/j.issn.1000-1328.2020.09.004

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Uncertainty Quantification Analysis and Application Research on  Cross  Flow Transition Model Parameters

XIANG Xing hao , ZHANG Yi feng , CHEN Jian qiang , YUAN Xian xu , CHEN Shu sheng   

  1. 1.State Key Laboratory of Aerodynamics of China Aerodynamics Research and Development Center, Mianyang 621000, China; 
    2. Computational Aerodynamics Institute of China Aerodynamics Research and Development Center, Mianyang 621000, China; 
    3. School of Aeronautics, Northwestern Polytechnical University, Xi ’an 710072, China
  • Received:2019-10-16 Revised:2020-02-28 Online:2020-09-15 Published:2020-09-27

Abstract: In order to obtain more accurate and reliable cross flow transition prediction results and to evaluate the influence of model parameters on transition prediction, the parameter uncertainty analysis and parameter sensitivity analysis of the cross flow transition model are carried out. Firstly, a fully localized cross flow transition model based on the  γ Re θt  transition model is implemented. Then, the numerical calculation of the S K flat plate and the swept wing example is carried out with the cross flow transition model using the Latin hypercube sampling method for the model parameters. The non intrusive polynomial chaos (NIPC) expansion method is used to quantitatively analyze the influence of the model parameters on different types of transition. Finally, based on the uncertainty and parameter sensitivity analysis results, the model parameters are filtrated and calibrated. The NLF(2) 0415 swept wing, 6:1 standard spheroid and DLR F4 wing body combination are calculated. The results show that the model parameter cross flow & surface roughness has the greatest influence on the transition position and surface friction coefficient. In several conditions, the model has a good prediction of the cross flow transition in 3-D boundary layer. 

Key words: Polynomial chaos expansion, Uncertainty analysis, Parameter sensitivity, Cross flow transition, Transition model

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