Flows of liquid4He due to oscillating grids

2017 ◽  
Vol 832 ◽  
pp. 578-599 ◽  
Author(s):  
P. Švančara ◽  
M. La Mantia
Keyword(s):  
Turbulent Flows ◽  
Particle Tracking Velocimetry ◽  
Reynolds Numbers ◽  
Quantized Vortices ◽  
Viscous Fluids ◽  
Statistical Distributions ◽  
Small Particles ◽  
Oscillating Grids ◽  
The Mean ◽  
Cryogenic Flows

We investigate cryogenic flows of liquid4He between two grids oscillating in phase, at temperatures ranging from approximately 1.3 to 2.5 K, resulting in suitably defined Reynolds numbers up to$10^{5}$. We specifically study the flow-induced motions of small particles suspended in the fluid by using the particle tracking velocimetry technique. We focus on turbulent flows of superfluid4He that occur below approximately 2.2 K and are known to display, in certain conditions, features different from those observed in flows of classical viscous fluids, such as water. We find that, at large enough length scales, larger than the mean distance between quantized vortices, representing the quantum length scale of the flow, the shapes of the velocity and velocity increment statistical distributions are very similar to those obtained in turbulent flows of viscous fluids. The experimental outcome strongly supports the view that, in the range of investigated parameters, particles probing flows of superfluid4He behave as if they were tracking classical flows.

Flight-crash events in superfluid turbulence

2019 ◽  
Vol 876 ◽  
Author(s):  
P. Švančara ◽  
M. La Mantia
Keyword(s):  
Turbulent Flows ◽  
Energy Transport ◽  
Quantized Vortices ◽  
Viscous Fluids ◽  
Superfluid Turbulence ◽  
Small Particles ◽  
Unique Type ◽  
Time Symmetry ◽  
Typical Particle ◽  
The Mean

We show experimentally that the mechanisms of energy transport in turbulent flows of superfluid $^{4}\text{He}$ are strikingly different from those occurring in turbulent flows of viscous fluids. We argue that the result can be related to the role played by quantized vortices in this unique type of turbulence. The flow-induced motions of relatively small particles suspended in the liquid reveal that, for scales of the order of the mean distance between the vortices, the particles do not tend on average to decelerate faster than they accelerate, whereas, at larger scales, a classical-like asymmetry is recovered. It follows that, in the range of investigated parameters, flight-crash events are less apparent than in classical turbulence. We specifically link the outcome to the time symmetry of quantized vortex reconnections observed at scales comparable to the typical particle size.

scholarly journals Natural logarithms

2013 ◽  
Vol 718 ◽  
pp. 1-4 ◽  
Author(s):  
B. J. McKeon
Keyword(s):  
Turbulent Flows ◽  
Reynolds Numbers ◽  
Streamwise Velocity ◽  
Wall Turbulence ◽  
Significant Advance ◽  
Mean Velocity ◽  
Velocity Fluctuations ◽  
Logarithmic Scaling ◽  
The Mean ◽  
High Reynolds

AbstractMarusic et al. (J. Fluid Mech., vol. 716, 2013, R3) show the first clear evidence of universal logarithmic scaling emerging naturally (and simultaneously) in the mean velocity and the intensity of the streamwise velocity fluctuations about that mean in canonical turbulent flows near walls. These observations represent a significant advance in understanding of the behaviour of wall turbulence at high Reynolds number, but perhaps the most exciting implication of the experimental results lies in the agreement with the predictions of such scaling from a model introduced by Townsend (J. Fluid Mech., vol. 11, 1961, pp. 97–120), commonly termed the attached eddy hypothesis. The elegantly simple, yet powerful, study by Marusic et al. should spark further investigation of the behaviour of all fluctuating velocity components at high Reynolds numbers and the outstanding predictions of the attached eddy hypothesis.

scholarly journals Reynolds number dependence of mean flow structure in square duct turbulence

2010 ◽  
Vol 644 ◽  
pp. 107-122 ◽  
Author(s):  
ALFREDO PINELLI ◽  
MARKUS UHLMANN ◽  
ATSUSHI SEKIMOTO ◽  
GENTA KAWAHARA
Keyword(s):  
Reynolds Number ◽  
Secondary Flow ◽  
Buffer Layer ◽  
Turbulent Flows ◽  
Reynolds Numbers ◽  
The Other ◽  
Streamwise Vorticity ◽  
Square Duct ◽  
Layer Structures ◽  
The Mean

We have performed direct numerical simulations of turbulent flows in a square duct considering a range of Reynolds numbers spanning from a marginal state up to fully developed turbulent states at low Reynolds numbers. The main motivation stems from the relatively poor knowledge about the basic physical mechanisms that are responsible for one of the most outstanding features of this class of turbulent flows: Prandtl's secondary motion of the second kind. In particular, the focus is upon the role of flow structures in its generation and characterization when increasing the Reynolds number. We present a two-fold scenario. On the one hand, buffer layer structures determine the distribution of mean streamwise vorticity. On the other hand, the shape and the quantitative character of the mean secondary flow, defined through the mean cross-stream function, are influenced by motions taking place at larger scales. It is shown that high velocity streaks are preferentially located in the corner region (e.g. less than 50 wall units apart from a sidewall), flanked by low velocity ones. These locations are determined by the positioning of quasi-streamwise vortices with a preferential sign of rotation in agreement with the above described velocity streaks' positions. This preferential arrangement of the classical buffer layer structures determines the pattern of the mean streamwise vorticity that approaches the corners with increasing Reynolds number. On the other hand, the centre of the mean secondary flow, defined as the position of the extrema of the mean cross-stream function (computed using the mean streamwise vorticity), remains at a constant location departing from the mean streamwise vorticity field for larger Reynolds numbers, i.e. it scales in outer units. This paper also presents a detailed validation of the numerical technique including a comparison of the numerical results with data obtained from a companion experiment.

A Continuous Prediction Method for Fully Developed Laminar, Transitional, and Turbulent Flows in Pipes

1975 ◽  
Vol 42 (1) ◽  
pp. 51-54 ◽  
Author(s):  
N. W. Wilson ◽  
R. S. Azad
Keyword(s):  
Turbulent Flows ◽  
Flow Characteristics ◽  
Prediction Method ◽  
Reynolds Numbers ◽  
Mean Flow ◽  
Number Range ◽  
Circular Pipes ◽  
The Mean ◽  
Single Set ◽  
Good Agreement

A single set of equations is developed to predict the mean flow characteristics in long circular pipes operating at laminar, transitional, and turbulent Reynolds numbers. Generally good agreement is obtained with available data in the Reynolds number range 100 < Re < 500,000.

Structure of Turbulent Flows Over Forward Facing Steps With Adverse Pressure Gradient

2016 ◽  
Vol 138 (11) ◽  
Author(s):  
Hassan Iftekhar ◽  
Martin Agelin-Chaab
Keyword(s):  
Reynolds Number ◽  
Pressure Gradient ◽  
Turbulent Flows ◽  
Large Scale ◽  
Adverse Pressure Gradient ◽  
Reynolds Numbers ◽  
Step Height ◽  
Reattachment Length ◽  
Mean Velocity ◽  
The Mean

This paper reports an experimental study on the effects of adverse pressure gradient (APG) and Reynolds number on turbulent flows over a forward facing step (FFS) by employing three APGs and three Reynolds numbers. A particle image velocimetry (PIV) technique was used to conduct velocity measurements at several locations downstream, and the flow statistics up to 68 step heights are reported. The step height was maintained at 6 mm, and the Reynolds numbers based on the step height and freestream mean velocity were 1600, 3200, and 4800. The mean reattachment length increases with the increase in Reynolds number without the APG whereas the mean reattachment length remains constant for increasing APG. The proper orthogonal decomposition (POD) results confirmed that higher Reynolds numbers caused the large-scale structures to be more defined and organized close to the step surface.

scholarly journals Turbulent boundary layers and channels at moderate Reynolds numbers

2010 ◽  
Vol 657 ◽  
pp. 335-360 ◽  
Author(s):  
JAVIER JIMÉNEZ ◽  
SERGIO HOYAS ◽  
MARK P. SIMENS ◽  
YOSHINORI MIZUNO
Keyword(s):  
Boundary Layer ◽  
Boundary Layers ◽  
Turbulent Flows ◽  
Pressure Fluctuations ◽  
Reynolds Numbers ◽  
Streamwise Velocity ◽  
Rotational Flow ◽  
Mean Velocity ◽  
The Mean ◽  
External Flows

The behaviour of the velocity and pressure fluctuations in the outer layers of wall-bounded turbulent flows is analysed by comparing a new simulation of the zero-pressure-gradient boundary layer with older simulations of channels. The 99 % boundary-layer thickness is used as a reasonable analogue of the channel half-width, but the two flows are found to be too different for the analogy to be complete. In agreement with previous results, it is found that the fluctuations of the transverse velocities and of the pressure are stronger in the boundary layer, and this is traced to the pressure fluctuations induced in the outer intermittent layer by the differences between the potential and rotational flow regions. The same effect is also shown to be responsible for the stronger wake component of the mean velocity profile in external flows, whose increased energy production is the ultimate reason for the stronger fluctuations. Contrary to some previous results by our group, and by others, the streamwise velocity fluctuations are also found to be higher in boundary layers, although the effect is weaker. Within the limitations of the non-parallel nature of the boundary layer, the wall-parallel scales of all the fluctuations are similar in both the flows, suggesting that the scale-selection mechanism resides just below the intermittent region, y/δ = 0.3–0.5. This is also the location of the largest differences in the intensities, although the limited Reynolds number of the boundary-layer simulation (Reθ ≈ 2000) prevents firm conclusions on the scaling of this location. The statistics of the new boundary layer are available from http://torroja.dmt.upm.es/ftp/blayers/.

Experiments on swirling turbulent flows. Part 1. Similarity in swirling flows

1973 ◽  
Vol 60 (4) ◽  
pp. 665-687 ◽  
Author(s):  
K. S. Yajnik ◽  
M. V. Subbaiah
Keyword(s):  
Turbulent Flows ◽  
Pipe Flow ◽  
Reynolds Numbers ◽  
Swirling Flows ◽  
Turbulent Pipe Flow ◽  
Extended Form ◽  
Mean Velocity ◽  
Swirl Angle ◽  
The Mean ◽  
Similarity Laws

The effects of swirl on internal turbulent flows are studied by conducting experiments on turbulent pipe flow with variable initial swirl. This first part of the study is primarily concerned with similarity laws. The mean velocity profiles, both away from and close to the wall, are found to admit similarity representations at sufficiently large Reynolds numbers, provided that flow reversal does not take place near the entrance. While the wall law is not sensibly dependent on swirl, the velocity defect law in its extended form is sensitive to swirl. Further, a logarithmic skin-friction law is obtained in which only the additive coefficient depends on swirl. This coefficient is found to vary linearly with the swirl angle in the range of the present experiments.

Assessing RANS Numerical and Modeling Properties in the Simulation of the Flow Around Captive and Moving Cylinders

2020 ◽  
Author(s):  
Rita M. Costa ◽  
Luís Eça ◽  
Arjen Koop
Keyword(s):  
Turbulent Flows ◽  
Unsteady Flows ◽  
Classical Problem ◽  
Reynolds Numbers ◽  
Time Signal ◽  
Time Averaging ◽  
Reynolds Stresses ◽  
Mean Flow ◽  
Ensemble Averaging ◽  
The Mean

Abstract In many Engineering applications, the Reynolds-Averaged Navier-Stokes (RANS) equations are still used to simulate high Reynolds numbers (turbulent) flows around complex geometries. In flows that exhibit significant regions of flow separation leading to vortex shedding, it does not make sense to define the mean flow using time-averaging. Therefore, the use of RANS (even if locally) in statistically unsteady flows requires the application of ensemble-averaging to the flow variables and to the mass and momentum equations, which generates the appearance of the Reynolds stresses. Turbulence models available in the open literature have been developed for the simulation of statistically steady flows (mean flow defined by time-averaging). Nonetheless, the same models are used for the simulation of statistically unsteady flows. Therefore, it is not guaranteed that such models provide sufficient diffusion (damping) to capture only the mean flow. In this paper, we have investigated the modeling and numerical properties of RANS supplemented by the k–ω SST eddy-viscosity model when applied to the classical problem of the flow around captive and moving (imposed motion) cylinders with Reynolds numbers ranging from 102 to 106. Two and three-dimensional simulations are performed and numerical (statistical, iterative and discretization) convergence properties are assessed for moving and deforming grids techniques. The quantities of interest are the drag and lift coefficients, for which we determine the frequency content of the time signal to assess if the numerical results correspond (as intended) to the mean flow. Results obtained at a Reynolds number of 104 are compared with experimental data available in the open literature.

Lattice Boltzmann for Turbulence Modeling

2018 ◽  
Author(s):  
Sauro Succi
Keyword(s):  
Turbulent Flows ◽  
Lattice Boltzmann ◽  
Turbulence Modeling ◽  
Real Life ◽  
Practical Interest ◽  
Reynolds Numbers ◽  
Full Resolution ◽  
To Come ◽  
Highly Turbulent Flows ◽  
Main Ideas

This chapter introduces the main ideas behind the application of LBE methods to the problem of turbulence modeling, namely the simulation of flows which contain scales of motion too small to be resolved on present-day and foreseeable future computers. Many real-life flows of practical interest exhibit Reynolds numbers far too high to be directly simulated in full resolution on present-day computers and arguably for many years to come. This raises the challenge of predicting the behavior of highly turbulent flows without directly simulating all scales of motion which take part to turbulence dynamics, but only those that fall within the computer resolution at hand.

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