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A century after Prandtl's mixing length hypothesis, full-profile scaling of the mixing length in pressure-gradient turbulent boundary layers (PG TBLs) remains debated, especially for adverse pressure gradients (APGs). This work presents a…

流体动力学 · 物理学 2026-04-30 Weitao Bi

The pressure gradient has a significant influence on the mean-flow properties of turbulent boundary layers. Conventional analytical studies on PG turbulent boundary layers are conducted separately for the viscous sub-layer and overlap layer…

流体动力学 · 物理学 2024-09-10 Tan-Tan Du , Jun Chen , Wei-Tao Bi , Zhen-Su She

A robust composite mean velocity profile is developed for turbulent boundary layers (TBLs) subjected to adverse pressure gradients (APGs), extending the composite formulation for generic pressure-gradient TBLs proposed by…

流体动力学 · 物理学 2026-03-26 Ahmad Zarei , Mitchell Lozier , Rahul Deshpande , Ivan Marusic

This study establishes a symmetry-based framework to quantify non-equilibrium processes in complex pressure gradient (PG) turbulent boundary layers (TBLs), using a Lie-group-informed dilation-symmetry-breaking formalism. We derive a…

流体动力学 · 物理学 2025-09-01 Wei-Tao Bi , Ke-Xin Zheng , Jun Chen , Zhen-Su She

In this study, a new well-resolved large-eddy-simulation (LES) of an incompressible near-equilibrium adverse-pressure-gradient (APG) turbulent boundary layer (TBL) over a flat plate is presented. In this simulation, we have established a…

流体动力学 · 物理学 2022-03-07 Ramon Pozuelo , Qiang Li , Philipp Schlatter , Ricardo Vinuesa

The statistical properties are presented for the direct numerical simulation (DNS) of a self-similar adverse pressure gradient (APG) turbulent boundary layer (TBL) at the verge of separation. The APG TBL has a momentum thickness based…

Coherent motions associated with extreme wall shear stress events are investigated for adverse pressure gradient turbulent boundary layers (APG-TBLs). The analyses are performed using wall-resolved large eddy simulations of a NACA0012…

流体动力学 · 物理学 2025-11-07 Leandro J. O. Silva , William R. Wolf

The prediction of turbulent boundary layer (TBL) flow over a convex surface as in aircraft wings or gas turbine blades is a challenging problem. Finding a universal scaling law of turbulence statistics of TBLs over a wide range of adverse…

流体动力学 · 物理学 2019-12-12 Atsushi Sekimoto , Vassili Kitsios , Callum Atkinson , Julio Soria

Two direct numerical simulation (DNS) databases are investigated to understand the effect of the outer-layer turbulence on the inner layer's structures and energy transfer mechanisms. The first DNS database is the non-equilibrium…

流体动力学 · 物理学 2024-07-25 Taygun R. Gungor , Yvan Maciel , Ayse G. Gungor

This study focuses on developing a predictive model for mean velocity profiles and total shear stress profiles in turbulent boundary layers subjected to adverse pressure gradients, especially with history effects. A new scaling using…

流体动力学 · 物理学 2025-11-03 Zhengqin Shu , Chunxiao Xu

This paper report on the design of an experiment to establish an experimental self-similar adverse pressure gradient (APG) turbulent boundary layer (TBL) flow at the verge of separation in order to characterise its statistical structure and…

流体动力学 · 物理学 2023-02-20 Muhammad Shehzad , Bihai Sun , Callum Atkinson , Julio Soria

This study uses high-fidelity simulations (DNS or LES) and experimental datasets to analyse the effect of non-equilibrium streamwise mean pressure gradients (adverse or favourable), including attached and separated flows, on the statistics…

流体动力学 · 物理学 2024-11-20 Saurabh Pargal , Junlin Yuan , Stephane Moreau

The convection velocity ($U_C$) of turbulent structures has been studied in adverse-pressure-gradient (APG) turbulent boundary layers (TBLs) for a wide range of Reynolds numbers $Re_\tau = 1400 - 4000$. The study is based on estimation of…

流体动力学 · 物理学 2022-11-23 Artur Dróżdż , Paweł Niegodajew , Mathias Romańczyk , Witold Elsner

The effect of a moderate adverse pressure gradient (APG) on the structure of a high-Reynolds-number turbulent boundary layer (TBL) was investigated experimentally using complementary multi-point measurements. Unlike many previous studies,…

流体动力学 · 物理学 2026-05-22 Mitchell Lozier , Ahmad Zarei , Ivan Marusic , Rahul Deshpande

An essential feature of canonical zero-pressure-gradient (ZPG) turbulent boundary layers (TBLs) is that the mean streamwise velocity exhibits a logarithmic dependence on the wall-normal distance, known as the log law. In this study, we…

流体动力学 · 物理学 2026-01-27 Fuzhou Lyu , Lihao Zhao , Weixi Huang , Chunxiao Xu

Turbulent boundary layers under adverse pressure gradients are studied using well-resolved large-eddy simulations (LES) with the goal of assessing the influence of the streamwise pressure development. Near-equilibrium boundary layers were…

流体动力学 · 物理学 2018-12-11 P. Schlatter , R. Vinuesa , A. Bobke , R. Örlü

A flat plate turbulent boundary layer (TBL) is experimentally subjected to a family of 22 favorable-adverse pressure gradients (FAPGs) by using a ceiling panel of variable convex curvature. We define a FAPG as a sequence of streamwise…

流体动力学 · 物理学 2022-11-17 Aadhy Parthasarathy , Theresa Saxton-Fox

Recently, Nagib et al (2024} utilized indicator functions of profiles of the streamwise normal stress to reveal the ranges of validity, in wall distance and Reynolds number, for each of two proposed models in DNS of channel and pipe flows.…

流体动力学 · 物理学 2024-11-20 Hassan Nagib , Ivan Marusic

Reynolds-number effects in the adverse-pressure-gradient (APG) turbulent boundary layer (TBL) developing on the suction side of a NACA4412 wing section are assessed in the present work. To this end, we analyze four cases at Reynolds numbers…

流体动力学 · 物理学 2019-04-17 R. Vinuesa , P. S. Negi , M. Atzori , A. Hanifi , D. S. Henningson , P. Schlatter

The direct measurement of wall shear stress in turbulent boundary layers (TBL) is challenging, therefore requiring it to be indirectly determined from mean profile measurements. Most popular methods assume the mean streamwise velocity to…

流体动力学 · 物理学 2021-12-14 Praveen Kumar , Krishnan Mahesh
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