On the mechanism of turbulent drag reduction with super-hydrophobic surfaces

2015 ◽  
Vol 773 ◽  
Author(s):  
Amirreza Rastegari ◽  
Rayhaneh Akhavan
Keyword(s):  
Reynolds Number ◽  
Surface Layer ◽  
Drag Reduction ◽  
Channel Flow ◽  
Free Fraction ◽  
Turbulent Channel Flow ◽  
Governing Equations ◽  
Turbulent Drag Reduction ◽  
Turbulent Drag ◽  
Effective Slip

The mechanism of turbulent drag reduction (DR) with super-hydrophobic (SH) surfaces is investigated by direct numerical simulation (DNS) and analysis of the governing equations in channel flow. The DNS studies were performed using lattice Boltzmann methods in channels with ‘idealized’ SH surfaces on both walls, comprised of longitudinal micro-grooves (MG), transverse MG, or micro-posts. DRs of $5\,\%$ to $83\,\%$, $-4\,\%$ to $20\,\%$, and $14\,\%$ to $81\,\%$ were realized in DNS with longitudinal MG, transverse MG, and micro-posts, respectively. By mathematical analysis of the governing equations, it is shown that, in SH channel flows with any periodic SH micro-pattern on the walls, the magnitude of DR can be expressed as $DR=U_{slip}/U_{bulk}+O({\it\varepsilon})$, where the first term represents the DR resulting from the effective slip on the walls, and the second term represents the DR or drag increase (DI) resulting from modifications to the turbulence dynamics and any secondary mean flows established in the SH channel compared to a channel flow with no-slip walls at the same bulk Reynolds number as the SH channel. Comparison of this expression to DNS results shows that, with all SH surface micro-patterns studied, between 80 % and 100 % of the DR in turbulent flow arises from the effective slip on the walls. Modifications to the turbulence dynamics contribute no more than 20 % of the total DR with longitudinal MG or micro-posts of high shear-free fraction (SFF), and a DI with transverse MG or micro-posts of moderate SFF. The effect of the SH surface on the normalized dynamics of turbulence is found to be small in all cases, and confined to additional production of turbulence kinetic energy (TKE) within a thin ‘surface layer’ of thickness of the order of the width of surface micro-indentations. Outside of this ‘surface layer’, the normalized dynamics of turbulence proceeds as in a turbulent channel flow with no-slip walls at the friction Reynolds number of the SH channel flow.

Simulation Results for Micro-Bubbles and Turbulent Drag Reduction (Keynote)

2003 ◽  
Author(s):  
M. R. Maxey ◽  
J. Xu ◽  
S. Dong ◽  
G. E. Karniadakis
Keyword(s):  
Drag Reduction ◽  
Numerical Simulations ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Turbulent Drag Reduction ◽  
Void Fractions ◽  
Turbulent Drag ◽  
Simulation Results ◽  
Small Bubbles ◽  
Near Wall

A series of numerical simulations of small bubbles seeded in a turbulent channel flow have been made at average void fractions up to 10%. Initial near-wall seeding in general leads to a transient reduction in drag while smaller bubbles are more effective in producing sustained drag reduction.

scholarly journals Prediction of Drag Reduction Rate in Turbulent Channel Flow Based on BP Neural Network

2020 ◽  
Vol 194 ◽  
pp. 05049
Author(s):  
Yuchen Cao ◽  
Yongwen Yang
Keyword(s):  
Neural Network ◽  
Drag Reduction ◽  
Polymer Solution ◽  
Channel Flow ◽  
Bp Neural Network ◽  
Reduction Rate ◽  
Turbulent Channel Flow ◽  
Solution Concentration ◽  
Turbulent Drag Reduction ◽  
Turbulent Drag

The technology of turbulent drag reduction by viscoelastic additives cannot be widely applied in practical engineering due to the difficulty in judging the effect of drag reduction. To solve this problem, the experiment of drag-reducing channel flow of polymer solution was carried out based on the comprehensive analysis of the factors affecting the drag reduction rate. Abundant drag reduction rate data were obtained. A three-layer BP neural network prediction model was established with polymer solution concentration, Reynolds number and injection flow rate as input parameters. Based on the test results, the prediction accuracy on drag reduction rate of the model was analysed. The prediction and model validation of drag reduction rate are carried out further according to the historical data in literature. The results show that the predicted drag reduction rate of BP neural network is close to the real drag reduction rate in the drag-reducing flow of polymer solution. The prediction is with high accuracy and with good generalization ability. It is expected to be applied to practical projects and to promote the development of turbulent drag reduction technology by additives.

scholarly journals Fibre-induced drag reduction

2008 ◽  
Vol 602 ◽  
pp. 209-218 ◽  
Author(s):  
J. J. J. GILLISSEN ◽  
B. J. BOERSMA ◽  
P. H. MORTENSEN ◽  
H. I. ANDERSSON
Keyword(s):  
Experimental Data ◽  
Numerical Simulation ◽  
Reynolds Number ◽  
Drag Reduction ◽  
Elastic Layer ◽  
Turbulent Drag Reduction ◽  
Rigid Polymer ◽  
Fibre Concentration ◽  
Induced Drag ◽  
Turbulent Drag

We use direct numerical simulation to study turbulent drag reduction by rigid polymer additives, referred to as fibres. The simulations agree with experimental data from the literature in terms of friction factor dependence on Reynolds number and fibre concentration. An expression for drag reduction is derived by adopting the concept of the elastic layer.

Predictions of the effective slip length and drag reduction with a lubricated micro-groove surface in a turbulent channel flow

2019 ◽  
Vol 874 ◽  
pp. 797-820 ◽  
Author(s):  
Jaehee Chang ◽  
Taeyong Jung ◽  
Haecheon Choi ◽  
John Kim
Keyword(s):  
Aspect Ratio ◽  
Drag Reduction ◽  
Numerical Simulations ◽  
Channel Flow ◽  
Slip Length ◽  
Turbulent Channel Flow ◽  
Solid Substrate ◽  
Direct Numerical Simulations ◽  
Effective Slip ◽  
Lubricant Viscosity

We perform direct numerical simulations of a turbulent channel flow with a lubricated micro-grooved surface to investigate the effects of this surface on the slip characteristics at the interface and the friction drag. The interface between water and lubricant is assumed to be flat, i.e. the surface-tension effect is neglected. The solid substrate, where a lubricant is infused, is composed of straight longitudinal grooves. The flow rate of water inside the channel is maintained constant, and a lubricant layer under the interface is shear driven by the turbulent water flow above. A turbulent channel flow with a superhydrophobic (i.e. air-lubricated) surface having the same solid substrate configuration is also simulated for comparison. The results show that the drag reduction with the liquid-infused surface highly depends on the lubricant viscosity as well as the groove width and aspect ratio. The amounts of drag reduction with the liquid-infused surfaces are not as good as those with superhydrophobic surfaces, but are still meaningfully large. For instance, the maximum drag reduction by the heptane-infused surface is approximately 13 % for a rectangular groove whose spanwise width and depth in wall units are 12 and 14.4, respectively, whereas a superhydrophobic surface with the same geometry results in a drag reduction of 21 %. The mean slip length normalized by the viscosity ratio and groove depth depends on the groove aspect ratio. The ratio of fluctuating spanwise slip length to the streamwise one is between 0.25 (ideal surface without groove structures) and 1 (i.e. isotropic slip), indicating that the slip is anisotropic. Using the Stokes flow assumption, the effective streamwise and spanwise slip lengths are expressed as a function of groove geometric parameters and lubricant viscosity. We also suggest a predictive model for drag reduction with the heptane-lubricated surface by combining the predicted effective slip lengths with the drag reduction formula used for riblets (Luchini et al., J. Fluid Mech., vol. 228, 1991, pp. 87–109). The predicted drag reductions are in good agreements with those from the present and previous direct numerical simulations.

Turbulent drag reduction in channel flow with viscosity stratified fluids

2018 ◽  
Vol 176 ◽  
pp. 260-265 ◽  
Author(s):  
Somayeh Ahmadi ◽  
Alessio Roccon ◽  
Francesco Zonta ◽  
Alfredo Soldati
Keyword(s):  
Drag Reduction ◽  
Channel Flow ◽  
Stratified Fluids ◽  
Turbulent Drag Reduction ◽  
Turbulent Drag

Numerical simulation of turbulent drag reduction using micro-bubbles

2002 ◽  
Vol 468 ◽  
pp. 271-281 ◽  
Author(s):  
JIN XU ◽  
MARTIN R. MAXEY ◽  
GEORGE EM KARNIADAKIS
Keyword(s):  
Drag Reduction ◽  
Numerical Simulations ◽  
Turbulent Channel Flow ◽  
Supporting Evidence ◽  
Average Volume ◽  
Turbulent Drag Reduction ◽  
Turbulent Drag ◽  
Spherical Bubbles ◽  
Small Bubbles ◽  
Over Time

While turbulent drag reduction through the injection of micro-bubbles into a turbulent boundary layer is well established in experiments, there is a lack of corresponding supporting evidence from direct numerical simulations. Here we report on a series of numerical simulations of small bubbles seeded in a turbulent channel flow at average volume fractions of up to 8%. These results show that even for relatively large bubbles, an initial transient drag reduction can occur as bubbles disperse into the flow. Relatively small spherical bubbles will produce a sustained level of drag reduction over time.

Sign in / Sign up

Export Citation Format

Share Document