Modification of near-wall turbulence structure in a shear-driven three-dimensional turbulent boundary layer

1998 ◽  
Vol 25 (3) ◽  
pp. 233-242 ◽  
Author(s):  
R. O. Kiesow ◽  
M. W. Plesniak
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Three Dimensional ◽  
Wall Turbulence ◽  
Turbulence Structure ◽  
Near Wall Turbulence ◽  
Near Wall

Near-wall structure of a turbulent boundary layer with riblets

1989 ◽  
Vol 208 ◽  
pp. 417-458 ◽  
Author(s):  
Kwing-So Choi
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Flow Visualization ◽  
Extensive Study ◽  
Wall Turbulence ◽  
Wall Structure ◽  
Turbulence Structure ◽  
Turbulent Drag ◽  
Wind Tunnel Study ◽  
Near Wall

A detailed wind tunnel study has been carried out on the near-wall turbulence structure over smooth and riblet wall surfaces under zero pressure gradient. Time-average quantities as ‘well as conditionally sampled profiles were obtained using hotwire/film anemometry, along with a simultaneous flow visualization using the smoke-wire technique and a sheet of laser light. The experimental results indicated a significant change of the structure in the turbulent boundary layer near the riblet surface. The change was confined within a small volume of the flow close to the wall surface. A conceptual model for the sequence of the bursts was then proposed based on an extensive study of the flow visualization, and was supported by the results of conditionally sampled velocity fields. A possible mechanism of turbulent drag reduction by riblets is discussed.

scholarly journals Metric for attractor overlap

2019 ◽  
Vol 874 ◽  
pp. 720-755 ◽  
Author(s):  
Rishabh Ishar ◽  
Eurika Kaiser ◽  
Marek Morzyński ◽  
Daniel Fernex ◽  
Richard Semaan ◽  
...  
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Three Dimensional ◽  
Particle Image Velocimetry Data ◽  
Open Loop ◽  
Operating Conditions ◽  
Wall Turbulence ◽  
Circular Cylinders ◽  
Two Dimensional ◽  
Starting Point

We present the first general metric for attractor overlap (MAO) facilitating an unsupervised comparison of flow data sets. The starting point is two or more attractors, i.e. ensembles of states representing different operating conditions. The proposed metric generalizes the standard Hilbert-space distance between two snapshot-to-snapshot ensembles of two attractors. A reduced-order analysis for big data and many attractors is enabled by coarse graining the snapshots into representative clusters with corresponding centroids and population probabilities. For a large number of attractors, MAO is augmented by proximity maps for the snapshots, the centroids and the attractors, giving scientifically interpretable visual access to the closeness of the states. The coherent structures belonging to the overlap and disjoint states between these attractors are distilled by a few representative centroids. We employ MAO for two quite different actuated flow configurations: a two-dimensional wake with vortices in a narrow frequency range and three-dimensional wall turbulence with a broadband spectrum. In the first application, seven control laws are applied to the fluidic pinball, i.e. the two-dimensional flow around three circular cylinders whose centres form an equilateral triangle pointing in the upstream direction. These seven operating conditions comprise unforced shedding, boat tailing, base bleed, high- and low-frequency forcing as well as two opposing Magnus effects. In the second example, MAO is applied to three-dimensional simulation data from an open-loop drag reduction study of a turbulent boundary layer. The actuation mechanisms of 38 spanwise travelling transversal surface waves are investigated. MAO compares and classifies these actuated flows in agreement with physical intuition. For instance, the first feature coordinate of the attractor proximity map correlates with drag for the fluidic pinball and for the turbulent boundary layer. MAO has a large spectrum of potential applications ranging from a quantitative comparison between numerical simulations and experimental particle-image velocimetry data to the analysis of simulations representing a myriad of different operating conditions.

Growth and breakdown of low-speed streaks leading to wall turbulence

2007 ◽  
Vol 586 ◽  
pp. 371-396 ◽  
Author(s):  
MASAHITO ASAI ◽  
YASUFUMI KONISHI ◽  
YUKI OIZUMI ◽  
MICHIO NISHIOKA
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Low Frequency ◽  
Wall Turbulence ◽  
Linear Stability Theory ◽  
Transition Flow ◽  
Wall Suction ◽  
Low Speed ◽  
Low Speed Streaks ◽  
Near Wall

Two-dimensional local wall suction is applied to a fully developed turbulent boundary layer such that near-wall turbulence structures are completely sucked out, but most of the turbulent vortices in the original outer layer can survive the suction and cause the resulting laminar flow to undergo re-transition. This enables us to observe and clarify the whole process by which the suction-surviving strong vortical motions give rise to near-wall low-speed streaks and eventually generate wall turbulence. Hot-wire and particle image velocimetry (PIV) measurements show that low-frequency velocity fluctuations, which are markedly suppressed near the wall by the local wall suction, soon start to grow downstream of the suction. The growth of low-frequency fluctuations is algebraic. This characterizes the streak growth caused by the suction-surviving turbulent vortices. The low-speed streaks obtain almost the same spanwise spacing as that of the original turbulent boundary layer without the suction even in the initial stage of the streak development. This indicates that the suction-surviving turbulent vortices are efficient in exciting the necessary ingredients for the wall turbulence, namely, low-speed streaks of the correct scale. After attaining near-saturation, the low-speed streaks soon undergo sinuous instability to lead to re-transition. Flow visualization shows that the streak instability and its subsequent breakdown occur at random in space and time in spite of the spanwise arrangement of streaks being almost periodic. Even under the high-intensity turbulence conditions, the sinuous instability amplifies disturbances of almost the same wavelength as predicted from the linear stability theory, though the actual growth is in the form of a wave packet with not more than two waves. It should be emphasized that the mean velocity develops the log-law profile as the streak breakdown proceeds. The transient growth and eventual breakdown of low-speed streaks are also discussed in connection with the critical condition for the wall-turbulence generation.

Particle image velocimetry investigation of a turbulent boundary layer manipulated by spanwise wall oscillations

2002 ◽  
Vol 467 ◽  
pp. 41-56 ◽  
Author(s):  
GAETANO MARIA DI CICCA ◽  
GAETANO IUSO ◽  
PIER GIORGIO SPAZZINI ◽  
MICHELE ONORATO
Keyword(s):  
Boundary Layer ◽  
Particle Image Velocimetry ◽  
Turbulent Boundary Layer ◽  
Particle Image ◽  
Oscillation Amplitude ◽  
Research Programme ◽  
Oscillation Period ◽  
Wall Turbulence ◽  
Image Velocimetry ◽  
Near Wall

Particle image velocimetry has been applied to the study of a canonical turbulent boundary layer and to a turbulent boundary layer forced by transversal wall oscillations. This work is part of the research programme at the Politecnico di Torino aerodynamic laboratory with the objective of investigating the response of near-wall turbulence to external perturbations. Results are presented for the optimum oscillation period of 100 viscous time units and for an oscillation amplitude of 320 viscous units. As expected, turbulent velocity fluctuations are considerably reduced by the wall oscillations. Particle image velocimetry has allowed comparisons between the canonical and forced flows in an attempt to find the physical mechanisms by which the wall oscillation influences the near-wall organized motions.

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