Closure to “Discussions of ‘Preston Tube Calibrations and Direct Force Floating Element Measurements in a Two-Dimensional Turbulent Boundary Layer’” (1982, ASME J. Fluids Eng., 104, pp. 160–161)

1982 ◽  
Vol 104 (2) ◽  
pp. 161-161
Author(s):  
J. E. McAllister ◽  
F. J. Pierce ◽  
M. H. Tennant
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Two Dimensional ◽  
Floating Element

Two-dimensional interaction between an incident shock and a turbulent boundary layer in the presence of an entropy layer

2011 ◽  
Vol 46 (6) ◽  
pp. 917-934 ◽  
Author(s):  
V. Ya. Borovoi ◽  
I. V. Egorov ◽  
A. Yu. Noev ◽  
A. S. Skuratov ◽  
I. V. Struminskaya
Keyword(s):  
Boundary Layer ◽  
Turbulent Boundary Layer ◽  
Incident Shock ◽  
Two Dimensional ◽  
Entropy Layer ◽  
Dimensional Interaction

The response of a turbulent boundary layer to lateral divergence

1979 ◽  
Vol 94 (2) ◽  
pp. 243-268 ◽  
Author(s):  
A. J. Smits ◽  
J. A. Eaton ◽  
P. Bradshaw
Keyword(s):  
Boundary Layer ◽  
Circular Cylinder ◽  
Turbulent Boundary Layer ◽  
Structural Parameters ◽  
Axial Flow ◽  
Turbulence Structure ◽  
Two Dimensional ◽  
Transition Section ◽  
Two Dimensional Flow ◽  
Made In

Measurements have been made in the flow over an axisymmetric cylinder-flare body, in which the boundary layer developed in axial flow over a circular cylinder before diverging over a conical flare. The lateral divergence, and the concave curvature in the transition section between the cylinder and the flare, both tend to destabilize the turbulence. Well downstream of the transition section, the changes in turbulence structure are still significant and can be attributed to lateral divergence alone. The results confirm that lateral divergence alters the structural parameters in much the same way as longitudinal curvature, and can be allowed for by similar empirical formulae. The interaction between curvature and divergence effects in the transition section leads to qualitative differences between the behaviour of the present flow, in which the turbulence intensity is increased everywhere, and the results of Smits, Young & Bradshaw (1979) for a two-dimensional flow with the same curvature but no divergence, in which an unexpected collapse of the turbulence occurred downstream of the curved region.

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.

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