推进技术 ›› 2014, Vol. 35 ›› Issue (3): 289-295.

• 气体动力学 总体 •    下一篇

基于DOE优化湍流模型的SERN分离点预测数值模拟与实验验证

王明涛1,2,徐惊雷1,于 洋1,范志鹏1,莫建伟1   

  1. 南京航空航天大学 能源与动力学院,江苏 南京 210016;南京航空航天大学 能源与动力学院,江苏 南京 210016;南京航空航天大学 能源与动力学院,江苏 南京 210016;南京航空航天大学 能源与动力学院,江苏 南京 210016;南京航空航天大学 能源与动力学院,江苏 南京 210016
  • 发布日期:2021-08-15
  • 作者简介:王明涛(1986—),男,硕士生,研究领域为发动机内流气动力学。E-mail:wangmingtao0930@sina.com 通讯作者:徐惊雷(1971—),男,博士,教授,研究领域为发动机内流气体动力学和实验流体力学。E-mail:xujl@nuaa.edu.cn
  • 基金资助:
    国家自然科学基金(90916023)。

Numerical Simulation and Experimental Validation of SERN Separation with Optimized Turbulence Model Based on DOE Method

  1. College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China;College of Energy and Power Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China
  • Published:2021-08-15

摘要: 在SERN(Simple expansion ramp nozzle)中,流动分离现象伴随着激波/边界层相互干扰、强剪切层、强激波等复杂的流动现象,导致通用的计算流体力学软件对SERN中分离点、分离区和再附点的计算精度不能满足工程需要。为了提高SERN中分离点的计算精度,基于Allamaprabhu等的研究成果,针对Menter的SST(Shear stress transport)模型,将修改湍流模型经验参数的方法运用到SERN分离流动的预测中,并利用试验设计(Design of experiment,DOE)优化方法得到了经验参数的最优组合,使计算和实验的无量纲分离点和无量纲分离点压力的误差分别降至1.99%,4.38%,压力分布均方根误差降至7.83%。 

关键词: 单臂膨胀喷管;流动分离;试验设计;湍流模型;经验参数 

Abstract: Flow separation in SERN (Single expansion ramp nozzle) is always accompanied with complex flow phenomena, such as shock wave/boundary layer interaction, the strong shear layer, and the strong shock wave. But, the common commercial CFD (Computational fluid dynamics) software still cannot satisfy the requirement of predicting accurately the separation point and reattachment point for engineering application. Based on the Menter’s SST (Shear stress transport) model, and the research results of Allamaprabhu et al., the turbulence empirical parameters are modified to predict the SERN separation flow more accurately, and the DOE (Design of experiment) method is further adopted to get the optimal combination parameters, so that the relative errors of the dimensionless separation point and the dimensionless static pressure distribution are reduced to 1.99% and 4.38%, respectively. And the root-mean-square error is also reduced to 7.83% between the experimental data and CFD results. 

Key words: SERN; Flow separation; Experiment design; Turbulence model;Empirical parameters