基于当地变量的横流转捩预测模型的研究与改进
收稿日期: 2015-04-01
修回日期: 2015-06-27
网络出版日期: 2015-07-17
基金资助
国家"973"计划(2014CB744804)
Study and modification of cross-flow induced transition model based on local variables
Received date: 2015-04-01
Revised date: 2015-06-27
Online published: 2015-07-17
Supported by
National Basic Research Program of China(2014CB744804)
Langtry和Menter提出的转捩预测模型需要改进以具备预测横流转捩的能力。当地变量Helicity参数可以指示边界层内的横流信息,因而可用来构造适用于复杂构型以及当代计算流体力学(CFD)并行计算的横流转捩预测模型。实现了基于Helicity参数的横流转捩预测模型,对于后掠角为45°的NLF(2)-0415无限展长后掠翼,模型能够预测不同雷诺数对横流转捩的影响,但是对6:1椭球的横流转捩预测结果与试验数据相差较多。针对实现的横流转捩预测模型的缺点,考虑横流速度因素进行改进。横流速度的求解经过简化近似可以当地求解,因而保证了改进的模型完全基于当地变量的优势。采用改进后的横流转捩预测模型分别对NLF(2)-0415机翼、6:1椭球以及DLR-F5机翼进行数值模拟,并与试验数据进行对比分析,结果显示改进后的横流转捩预测模型可以较为准确地捕捉横流转捩现象。
史亚云 , 白俊强 , 华俊 , 杨体浩 . 基于当地变量的横流转捩预测模型的研究与改进[J]. 航空学报, 2016 , 37(3) : 780 -789 . DOI: 10.7527/S1000-6893.2015.0194
The transition prediction model proposed by Langtry and Menter needs to be modified for predicting cross-flow induced transition. Local variable Helicity is found to be capable of indicating cross-flow information in the boundary layer, so it can be used to construct cross-flow transition prediction which is compatible with complex configuration and modern computational fluid dynamics(CFD) parallelized computation. The cross-flow transition prediction model based on Helicity parameter is realized and has the ability to capture the influence of different Reynolds numbers for infinite swept wing NLF(2)-0415 with sweep angle of 45°. However, the difference between the realized model result and experimental data for 6:1 prolate spheroid is large. In this paper, cross velocity factor is considered to modify the realized model aimed at improving the shortcoming of realized model. The solver of cross velocity is simplified and approximated for local calculation, which makes the modified cross-flow model retain the superiority of totally using only local variables. Finally, NLF(2)-0415 wing, 6:1 prolate spheroid and DLR-F5 wing are simulated by the modified model. The comparison between the simulation and experiment data indicates that the modified cross-flow transition prediction model can capture cross-flow induced transition phenomenon.
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