A data assimilation methodology for reconstructing turbulent flows around aircraft

作者：Kato Hiroshi^*; Yoshizawa Akira; Ueno Genta; Obayashi Shigeru

来源：Journal of Computational Physics, 2015, 283: 559-581.

DOI：10.1016/j.jcp.2014.12.013

• Turbulent flows
• Uncertainty
• Data assimilation
• Optimization

This paper proposes a new approach for the study of complex turbulent flows of aeronautics that integrates experimental fluid dynamics (EFD), employing methods such as wind tunnel experiments, and computational fluid dynamics (CFD) by using a data assimilation technique. The approach aims at representing complex turbulent flows more properly than conventional EFD and CFD approaches by estimating the proper angle of attack, the proper Mach number, and the proper turbulent viscosity, which are the three uncertainty factors in EFD and CFD. To this end, the ensemble transform Kalman filter (ETKF), a sequential advanced data assimilation method, is employed for the estimation and applied to transonic flows around the RAE 2822 airfoil (two-dimensional flow) and transonic flows around the ONERA M6 wing (three-dimensional flow). The results computed using the angles of attack, Mach numbers, and turbulent viscosities estimated by the ETKF diminish the discrepancies between the results of standard computations and experiments. These findings show the effectiveness of this approach, which combines EFD and CFD using data assimilation to represent complex turbulent flows.

• 出版日期2015-2-15