Drag reduction potentials of turbulence manipulation in adverse pressure gradient flows

AIAA Journal ◽  
1988 ◽  
Vol 26 (3) ◽  
pp. 367-368 ◽  
Author(s):  
B. van den Berg
2009 ◽  
Vol 48 (4) ◽  
pp. 663-677 ◽  
Author(s):  
Brian Brzek ◽  
Donald Chao ◽  
Özden Turan ◽  
Luciano Castillo

2019 ◽  
Author(s):  
Katherine K. Disser ◽  
Thomas C. Corke ◽  
Flint O. Thomas ◽  
Alan Duong ◽  
Samaresh Midya

2011 ◽  
Vol 681 ◽  
pp. 537-566 ◽  
Author(s):  
ROMAIN MATHIS ◽  
NICHOLAS HUTCHINS ◽  
IVAN MARUSIC

A model is proposed with which the statistics of the fluctuating streamwise velocity in the inner region of wall-bounded turbulent flows are predicted from a measured large-scale velocity signature from an outer position in the logarithmic region of the flow. Results, including spectra and all moments up to sixth order, are shown and compared to experimental data for zero-pressure-gradient flows over a large range of Reynolds numbers. The model uses universal time-series and constants that were empirically determined from zero-pressure-gradient boundary layer data. In order to test the applicability of these for other flows, the model is also applied to channel, pipe and adverse-pressure-gradient flows. The results support the concept of a universal inner region that is modified through a modulation and superposition of the large-scale outer motions, which are specific to the geometry or imposed streamwise pressure gradient acting on the flow.


1996 ◽  
Vol 118 (3) ◽  
pp. 514-519 ◽  
Author(s):  
F. R. Menter

The performance of recently developed eddy-viscosity turbulence models, including the author’s SST model, is evaluated against a number of attached and separated adverse pressure gradient flows. The results are compared in detail against experimental data, as well as against the standard k-ε model. Grid convergence was established for all computations. The study involves four different, state-of-the-art finite difference (finite volume) codes.


2011 ◽  
Vol 670 ◽  
pp. 581-605 ◽  
Author(s):  
GUILLERMO ARAYA ◽  
LUCIANO CASTILLO ◽  
CHARLES MENEVEAU ◽  
KENNETH JANSEN

A dynamic method for prescribing realistic inflow boundary conditions is presented for simulations of spatially developing turbulent boundary layers. The approach is based on the rescaling–recycling method proposed by Lund, Wu & Squires (J. Comput. Phys, vol. 140, 1998, pp. 233–258) and the multi-scale method developed by Araya, Jansen & Castillo (J. Turbul., vol. 10, no. 36, 2009, pp. 1–33). The rescaling process requires prior knowledge about how the velocity and length scales are related between the inlet and recycle stations. Here a dynamic approach is proposed in which such information is deduced dynamically by involving an additional plane, the so-called test plane located between the inlet and recycle stations. The approach distinguishes between the inner and outer regions of the boundary layer and enables the use of multiple velocity scales. This flexibility allows applications to boundary layer flows with pressure gradients and avoids the need to prescribe empirically the friction velocity and other flow parameters at the inlet of the domain. The dynamic method is tested in direct numerical simulations of zero, favourable and adverse pressure gradient flows. The dynamically obtained scaling exponents for the downstream evolution of boundary layer parameters are found to fluctuate in time, but on average they agree with the expected values for zero, favourable and adverse pressure gradient flows. Comparisons of the results with data from experiments, and from other direct numerical simulations that use much longer computational domains to capture laminar-to-turbulence transition, demonstrate the suitability of the proposed dynamic method.


2004 ◽  
Vol 126 (3) ◽  
pp. 297-304 ◽  
Author(s):  
Luciano Castillo ◽  
Xia Wang ◽  
William K. George

By using the RANS boundary layer equations, it will be shown that the outer part of an adverse pressure gradient turbulent boundary layer tends to remain in equilibrium similarity, even near and past separation. Such boundary layers are characterized by a single and constant pressure gradient parameter, Λ, and its value appears to be the same for all adverse pressure gradient flows, including those with eventual separation. Also it appears from the experimental data that the pressure gradient parameter, Λθ, is also approximately constant and given by Λθ=0.21±0.01. Using this and the integral momentum boundary layer equation, it is possible to show that the shape factor at separation also has to within the experimental uncertainty a single value: Hsep≅2.76±0.23. Furthermore, the conditions for equilibrium similarity and the value of Hsep are shown to be in reasonable agreement with a variety of experimental estimates, as well as the predictions from some other investigators.


1968 ◽  
Vol 31 (3) ◽  
pp. 547-582 ◽  
Author(s):  
M. C. Good ◽  
P. N. Joubert

Measurements of the distributions of pressure on a bluff flat plate (fence) have been correlated with the characteristics of the smooth-wall boundary layer in which it is immersed. For zero pressure-gradient flows, correlations are obtained for the variation of form drag with plate heighthwhich are analogous in form to the ‘law of the wall’ and the ‘velocity-defect law’ for the boundary-layer velocity profile. The data for adverse pressure-gradient flows is suggestive of a ‘law of the wake’ type correlation. Pressures on the upstream face of the bluff-plate are determined by a wall-similarity law, even forh/δ > 1, and are independent of the pressure-gradient history of the flow; the separation induced upstream is apparently of the Stratford-Townsend type. The effects of the history of the boundary layer are manifested only in the flow in the rear separation bubble, and then only forh/δ > ½. The base pressure is also sensitive to free-stream pressure gradients downstream of the bluff-plate. The relative extent of upstream influence of the bluff-plate on the boundary layer is found to increase rapidly ash/δ decreases. One set of measurements of the mean flow field is also presented.


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