@article{oai:jaxa.repo.nii.ac.jp:00022711,
 author = {加藤, 博司 and 石向, 桂一 and 吉澤, 徴 and Kato, Hiroshi and Ishiko, Keiichi and Yoshizawa, Akira},
 issue = {5},
 journal = {AIAA Journal},
 month = {Mar},
 note = {This study proposes a data assimilation methodology for estimating the optimal parameter values of turbulence models. The proposed methodology was applied to the estimation of the parameter a(sub 1) in the modified Menter k-ω shear-stress transport turbulence model. For this purpose, a fundamental turbulent flow, namely, the flow over a two-dimensional backward-facing step, was employed. The estimated value of a(sub 1) (1.0) differed from its original value (i.e., 0.31). The modified Menter k-ω shear-stress transport turbulence model with a(sub 1) = 1.0 was validated on several turbulent flow calculations; flows over a two-dimensional backward-facing step and a two-dimensional flat-plate boundary layer, two-dimensional transonic flows around the RAE 2822 airfoil, and three-dimensional transonic flows around the ONERA M6 wing. In simulations, the modified Menter k-ω shear-stress transport turbulence model with a(sub 1) = 1.0 better modeled the separated and adverse pressure gradient flows than the original modified Menter k-ω shear-stress transport turbulence model with a(sub 1) = 0.31. Furthermore, in the absence of separation and adverse pressure gradient flows, the proposed and original modified Menter k-ω shear-stress transport turbulence models computed almost the same results. These observations suggest that the proposed data assimilation methodology effectively estimates the optimal parameter values of turbulence models and that the estimated a(sub 1) (1.0) improves the performance of the modified Menter k-ω shear-stress transport turbulence model over the original value (i.e., 0.31)., 形態: カラー図版あり, Physical characteristics: Original contains color illustrations, 資料番号: PA1620004000},
 pages = {1512--1523},
 title = {Optimization of Parameter Values in the Turbulence Model Aided by Data Assimilation},
 volume = {54},
 year = {2016}
}