A data assimilation methodology for reconstructing turbulent flows around aircraft
A data assimilation methodology for reconstructing turbulent flows around aircraft
复制标题
DOI：
10.1016/j.jcp.2014.12.013
复制
发表时间：
2015-02-15
影响因子：
4.1
通讯作者：
Obayashi, Shigeru
中科院分区：
文献类型：
--
作者：
Kato, Hiroshi;Yoshizawa, Akira;Obayashi, Shigeru
本文提出了一种新的方法来研究复杂的航空湍流流动，集成实验流体动力学（EFD），采用风洞实验等方法，计算流体动力学（CFD），使用数据同化技术。该方法的目的是通过估计EFD和CFD中的三个不确定性因素--适当的攻角、适当的马赫数和适当的湍流粘度，比传统的EFD和CFD方法更恰当地表示复杂的湍流流动。为此，集合变换卡尔曼滤波器（ETKF），一个连续的先进的数据同化方法，用于估计和应用到跨音速绕流RAE 2822翼型（二维流）和跨音速绕流ONERA M6机翼（三维流）。使用ETKF估算的攻角、马赫数和湍流粘度计算的结果减小了标准计算结果与实验结果之间的差异。这些发现表明了这种方法的有效性，它结合了EFD和CFD使用数据同化来表示复杂的湍流。(C)2014 Elsevier Inc.保留所有权利。
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. (C) 2014 Elsevier Inc. Allrightsreserved.