Scaling law and a new LES wall-model for adverse-pressure-gradient turbulent boundary layer flow

2023 Fiscal Year Final Research Report

• Project/Area Number: 21K03876
• Research Category: Grant-in-Aid for Scientific Research (C)
• Allocation Type: Multi-year Fund
• Section: 一般
• Review Section: Basic Section 19010:Fluid engineering-related
• Research Institution: Okayama University
• Principal Investigator: Sekimoto Atsushi 岡山大学, 環境生命自然科学学域, 准教授 (00814485)
• Project Period (FY): 2021-04-01 – 2024-03-31
• Keywords: 逆圧力勾配乱流境界層 / LES / スケーリング則 / 流動制御

Outline of Final Research Achievements

Using direct numerical simulation (DNS) for turbulent boundary layers under adverse pressure gradients, we proposed a new scaling law for turbulent statistics. Instead of the conventional 99% thickness, we introduced a boundary layer thickness based on mean shear. We confirmed that turbulent statistics in the inertial region align well between zero pressure gradient boundary layers and those at the verge of separation. Additionally, we derived scaling laws for energy dissipation rate and vorticity magnitude based on the local equilibrium hypothesis. We validated them using DNS data, aiming to develop a novel wall model for LES. Furthermore, we advanced research on the influence and control of secondary flows (flows perpendicular to the main flow) caused by sidewalls. We demonstrated the potential to control secondary flow patterns using deep reinforcement learning.

Free Research Field

流体工学，乱流，データ駆動計算

Academic Significance and Societal Importance of the Research Achievements

逆圧力勾配下の乱流境界層において新たに提唱したスケーリング則の検証は学術的に重要で， 従来の99%厚さに代えて平均せん断に基づく境界層厚さを導入することで, 乱流統計量の正確な評価が可能となり, 境界層乱流の理解が深まる。さらに， LES壁モデルの精度向上と高速化が期待でき， 航空機やタービン翼など流体機械の性能向上への応用が挙げられる。新たなスケーリング則とそのLESシミュレーション技術は, 複雑形状周りの流れの正確な解析を可能にし, エネルギー効率の向上や環境負荷の低減に寄与する。また, 深層強化学習を用いた流れの制御技術は, 将来的な乱流制御の革新に繋がる可能性がある。