Innovative study toward prediction of friction drag at rough surfaces based on the investigation of the turbulent transport mechanisms by the volume averaging theory

2020 Fiscal Year Final Research Report

• Project/Area Number: 17K14591
• Research Category: Grant-in-Aid for Young Scientists (B)
• Allocation Type: Multi-year Fund
• Research Field: Fluid engineering
• Research Institution: Osaka Prefecture University
• Principal Investigator: Yusuke Kuwata 大阪府立大学, 工学(系)研究科(研究院), 助教 (40772851)
• Project Period (FY): 2017-04-01 – 2021-03-31
• Keywords: 粗面乱流 / 乱流モデル / 直接数値解析 / 空間・時間平均系 / 格子ボルツマン法

Outline of Final Research Achievements

Two types of the mathematical model are developed to predict friction drag at a rough surface by means of the direct numerical simulations by the supercomputer. Both models do not resolve the microscopic roughness structure but take account of the macroscopic effects by the wall roughness. One of the models predicts turbulence near a rough surface without resolving the roughness geometry. The other predicts a mean flow near a rough surface without resolving a time-dependent turbulent flow nor roughness geometry. It is confirmed that both models can accurately predict friction drag for various types of rough surfaces.

Free Research Field

乱流工学

Academic Significance and Societal Importance of the Research Achievements

実在する壁面は表面に生じる粗さの影響を受けるために，流体力学的な理想的滑面とみなすことができない場合が多い．しかし，その粗さの形状は様々であり，汎用的に粗さ効果を予測することは一般的に難しい．本研究では，粗さ高さに関する幾何パラメータを用いる既往の代数的なモデルでは無く，モデル化された粗さ効果を含んだ流動方程式を解くモデルを提案した．本モデルは，既往モデルとは大きく異なり，様々な流動条件・粗さ形状に対して汎用的に使用することができる．