scholarly journals One-point statistics for turbulent pipe flow up to

2021 ◽  
Vol 926 ◽  
Author(s):  
Sergio Pirozzoli ◽  
Joshua Romero ◽  
Massimiliano Fatica ◽  
Roberto Verzicco ◽  
Paolo Orlandi
Keyword(s):  
Turbulent Flows ◽  
Pipe Flow ◽  
Stokes Equations ◽  
Plug Flow ◽  
Circular Cross Section ◽  
Reynolds Numbers ◽  
Turbulent Pipe Flow ◽  
Asymptotic State ◽  
Mean Velocity ◽  
Velocity Variance

We study turbulent flows in a smooth straight pipe of circular cross-section up to friction Reynolds number $({\textit {Re}}_{\tau }) \approx 6000$ using direct numerical simulation (DNS) of the Navier–Stokes equations. The DNS results highlight systematic deviations from Prandtl friction law, amounting to approximately $2\,\%$ , which would extrapolate to approximately $4\,\%$ at extreme Reynolds numbers. Data fitting of the DNS friction coefficient yields an estimated von Kármán constant $k \approx 0.387$ , which nicely fits the mean velocity profile, and which supports universality of canonical wall-bounded flows. The same constant also applies to the pipe centreline velocity, thus providing support for the claim that the asymptotic state of pipe flow at extreme Reynolds numbers should be plug flow. At the Reynolds numbers under scrutiny, no evidence for saturation of the logarithmic growth of the inner peak of the axial velocity variance is found. Although no outer peak of the velocity variance directly emerges in our DNS, we provide strong evidence that it should appear at ${\textit {Re}}_{\tau } \gtrsim 10^4$ , as a result of turbulence production exceeding dissipation over a large part of the outer wall layer, thus invalidating the classical equilibrium hypothesis.

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.

Asymptotic scaling in turbulent pipe flow

2007 ◽  
Vol 365 (1852) ◽  
pp. 771-787 ◽  
Author(s):  
B.J McKeon ◽  
J.F Morrison
Keyword(s):  
Asymptotic Behaviour ◽  
Pipe Flow ◽  
Physical Space ◽  
Reynolds Numbers ◽  
Streamwise Velocity ◽  
Turbulent Pipe Flow ◽  
Inertial Subrange ◽  
Velocity Spectrum ◽  
Mean Velocity ◽  
High Reynolds

The streamwise velocity component in turbulent pipe flow is assessed to determine whether it exhibits asymptotic behaviour that is indicative of high Reynolds numbers. The asymptotic behaviour of both the mean velocity (in the form of the log law) and that of the second moment of the streamwise component of velocity in the outer and overlap regions is consistent with the development of spectral regions which indicate inertial scaling. It is shown that an ‘inertial sublayer’ in physical space may be considered as a spatial analogue of the inertial subrange in the velocity spectrum and such behaviour only appears for Reynolds numbers R + >5×10 3 , approximately, much higher than was generally thought.

Large Eddy Simulation of Fully Developed Turbulent Pipe Flow

2004 ◽  
Author(s):  
Sowjanya Vijiapurapu ◽  
Jie Cui
Keyword(s):  
Reynolds Number ◽  
Pipe Flow ◽  
Reynolds Numbers ◽  
Grid Resolution ◽  
Turbulent Pipe Flow ◽  
Scale Model ◽  
Subgrid Scale ◽  
Mean Velocity ◽  
Fine Mesh ◽  
Large Eddy

Fully developed turbulent pipe flow is investigated by large eddy simulations (LES). The three-dimensional, unsteady, incompressible, filtered continuity and Navier-Stokes equations in cylindrical coordinates are discretized by a finite difference method. The spatial derivatives are approximated by second order conservative schemes. This scheme eliminates the numerical generation or dissipation of energy. The pressure Poisson equation is solved by FFT method and time is advanced through a third order Runge-Kutta method. The commonly used subgrid scale (SGS) models — the Smagorinsky model and the dynamic model are implemented and simulations are performed for fully developed turbulent pipe flow at two different Reynolds numbers. The flow features in terms of mean velocity as well as higher order turbulence intensities and correlations are presented and compared to experimental and DNS data available in literature. Extensive comparisons are made for cases using different grid resolution, different streamwise domain dimension, different sub-grid scale model, and, at two different Reynolds number. For two Reynolds numbers (5,000 and 30,000) tested in this study, the fine mesh (64 × 96 × 64, circumferential × radial × longitudinal) produces better results than the coarse mesh (32 × 48 × 32), indicating the significance of the grid resolution, especially near the pipe surface. On the fine mesh for the two Reynolds numbers, the results exhibit a slight Reynolds number effect, indicating the mesh needs to be further refined at higher Reynolds number. Simulations were performed for two domain sizes, namely 6D and 12D, where D is the pipe diameter. When the streamwise grid resolution remains unchanged, the two simulations show negligible difference. This ensures that a 6D domain is adequate to include the largest eddies in a fully developed turbulent pipe flow at the current Reynolds number. When the fine mesh is used, the subgrid scale models (Smagorinsky and Dynamic) provide limited contribution to the total turbulent kinetic energy. Although the current results agree quite well with other published LES simulations, when compared with the Law of the wall, benchmark experiments and DNS results, the simulated mean velocity in the log region is higher than the experimental and DNS data. Overall, it was observed that the numerical methods work satisfactorily well for turbulent pipe flows at low and high Reynolds numbers, and, the method has capability to be used in the simulation of flows with practical interest.

Nonasymptotic behavior of developing turbulent pipe flow

1976 ◽  
Vol 54 (3) ◽  
pp. 268-278 ◽  
Author(s):  
J. K. Reichert ◽  
R. S. Azad
Keyword(s):  
Reynolds Number ◽  
Pipe Flow ◽  
Reynolds Numbers ◽  
Peak Position ◽  
Turbulent Pipe Flow ◽  
Shear Stresses ◽  
Mean Velocity ◽  
Inlet Region ◽  
The Mean ◽  
Hot Film

Detailed measurements of mean velocity U profiles, in the inlet 70 diameters of a pipe, show that the development of turbulent pipe flow is nonasymptotic. Experiments were done at seven Reynolds numbers in the range 56 000–15 3000. Contours of U and V fields are presented for two representative Reynolds numbers. A U component peak exceeding the fully developed values has been found to occur along the pipe centerline. The Reynolds number behavior of the peak position has been determined. Hot film measurements of the mean wall shear stresses in the inlet region also show a nonasymptotic development consistent with the mean velocity results.

Stability of Hagen-Poiseuille flow with superimposed rigid rotation

1976 ◽  
Vol 73 (1) ◽  
pp. 153-164 ◽  
Author(s):  
P.-A. Mackrodt
Keyword(s):  
Poiseuille Flow ◽  
Pipe Flow ◽  
Stokes Equations ◽  
Three Dimensional ◽  
Reynolds Numbers ◽  
Neutral Curve ◽  
Rigid Rotation ◽  
Transition To Turbulence ◽  
Navier Stokes ◽  
Navier Stokes Equations

The linear stability of Hagen-Poiseuille flow (Poiseuille pipe flow) with superimposed rigid rotation against small three-dimensional disturbances is examined at finite and infinite axial Reynolds numbers. The neutral curve, which is obtained by numerical solution of the system of perturbation equations (derived from the Navier-Stokes equations), has been confirmed for finite axial Reynolds numbers by a few simple experiments. The results suggest that, at high axial Reynolds numbers, the amount of rotation required for destabilization could be small enough to have escaped notice in experiments on the transition to turbulence in (nominally) non-rotating pipe flow.

scholarly journals Dynamics of viscoelastic pipe flow at low Reynolds numbers in the maximum drag reduction limit

2019 ◽  
Vol 874 ◽  
pp. 699-719 ◽  
Author(s):  
Jose M. Lopez ◽  
George H. Choueiri ◽  
Björn Hof
Keyword(s):  
Drag Reduction ◽  
Turbulent Flows ◽  
Pipe Flow ◽  
Domain Size ◽  
Reynolds Numbers ◽  
Weissenberg Number ◽  
Pipe Length ◽  
Low Reynolds Numbers ◽  
Maximum Drag Reduction ◽  
Low Reynolds

Polymer additives can substantially reduce the drag of turbulent flows and the upper limit, the so-called state of ‘maximum drag reduction’ (MDR), is to a good approximation independent of the type of polymer and solvent used. Until recently, the consensus was that, in this limit, flows are in a marginal state where only a minimal level of turbulence activity persists. Observations in direct numerical simulations at low Reynolds numbers ($Re$) using minimal sized channels appeared to support this view and reported long ‘hibernation’ periods where turbulence is marginalized. In simulations of pipe flow at $Re$ near transition we find that, indeed, with increasing Weissenberg number ($Wi$), turbulence expresses long periods of hibernation if the domain size is small. However, with increasing pipe length, the temporal hibernation continuously alters to spatio-temporal intermittency and here the flow consists of turbulent puffs surrounded by laminar flow. Moreover, upon an increase in $Wi$, the flow fully relaminarizes, in agreement with recent experiments. At even larger $Wi$, a different instability is encountered causing a drag increase towards MDR. Our findings hence link earlier minimal flow unit simulations with recent experiments and confirm that the addition of polymers initially suppresses Newtonian turbulence and leads to a reverse transition. The MDR state on the other hand results at these low$Re$ from a separate instability and the underlying dynamics corresponds to the recently proposed state of elasto-inertial turbulence.

Comparison of a Nonlinear k-ε Turbulence Closure Model With Stress Transport Models

1993 ◽  
Author(s):  
Muhammad A. R. Sharif ◽  
Yat-Kit E. Wong
Keyword(s):  
Pipe Flow ◽  
Flow Problem ◽  
Swirling Flow ◽  
Transport Model ◽  
Turbulent Pipe Flow ◽  
Turbulence Closure ◽  
Closure Model ◽  
Transport Models ◽  
Mean Velocity ◽  
Turbulence Closure Model

Abstract The performance of a nonlinear k-ϵ turbulence closure model (NKEM), in the prediction of isothermal incompressible turbulent flows, is compared with that of the stress transport models such as the differential Reynolds stress transport model (RSTM) and the algebraic stress transport model (ASTM). Fully developed turbulent pipe flow and confined turbulent swirling flow with a central non-swirling jet are numerically predicted using the Marker and Cell (MAC) finite difference method. Comparison of the prediction with the experiment show that all three models perform reasonably well for the pipe flow problem. For the swirling flow problem, the RSTM and ASTM is superior than the NKEM. RSTM and ASTM provide good agreement with measured mean velocity profiles. However, the turbulent stresses are over- or under-predicted. NKEM performs badly in prediction of mean velocity as well as the turbulent stresses.

Reconsideration of spanwise rotating turbulent channel flows via resolvent analysis

2018 ◽  
Vol 861 ◽  
pp. 200-222 ◽  
Author(s):  
Satoshi Nakashima ◽  
Mitul Luhar ◽  
Koji Fukagata
Keyword(s):  
Turbulent Flows ◽  
Stokes Equations ◽  
Turbulent Channel Flow ◽  
Reynolds Numbers ◽  
High Gain ◽  
Spectral Space ◽  
Rotation Rates ◽  
Wide Range ◽  
Effects Of Rotation ◽  
Spanwise Rotation

We study the effect of spanwise rotation in turbulent channel flow at both low and high Reynolds numbers by employing the resolvent formulation proposed by McKeon & Sharma (J. Fluid Mech., vol. 658, 2010, pp. 336–382). Under this formulation, the nonlinear terms in the Navier–Stokes equations are regarded as a forcing that acts upon the remaining linear dynamics to generate the turbulent velocity field in response. A gain-based decomposition of the forcing–response transfer function across spectral space yields models for highly amplified flow structures, or modes. Unlike linear stability analysis, this enables targeted analyses of the effects of rotation on high-gain modes that serve as useful low-order models for dynamically important coherent structures in wall-bounded turbulent flows. The present study examines a wide range of rotation rates. A posteriori comparisons at low Reynolds number ($\mathit{Re}_{\unicode[STIX]{x1D70F}}=180$) demonstrate that the resolvent formulation is able to quantitatively predict the effect of varying spanwise rotation rates on specific classes of flow structure (e.g. the near-wall cycle) as well as energy amplification across spectral space. For fixed inner-normalized rotation number, the effects of rotation at varying friction Reynolds numbers appear to be similar across spectral space, when scaled in outer units. We also consider the effects of rotation on modes with varying speed (i.e. modes that are localized in regions of varying mean shear), and provide suggestions for modelling the nonlinear forcing term.

scholarly journals Stochastic Dynamical Modeling of Turbulent Flows

2020 ◽  
Vol 3 (1) ◽  
pp. 195-219 ◽  
Author(s):  
A. Zare ◽  
T.T. Georgiou ◽  
M.R. Jovanović
Keyword(s):  
Turbulent Flows ◽  
High Performance ◽  
Degrees Of Freedom ◽  
Stokes Equations ◽  
Measurement Techniques ◽  
Large Data ◽  
Low Rank ◽  
Structural Constraints ◽  
Mean Velocity ◽  
Linearized Model

Advanced measurement techniques and high-performance computing have made large data sets available for a range of turbulent flows in engineering applications. Drawing on this abundance of data, dynamical models that reproduce structural and statistical features of turbulent flows enable effective model-based flow control strategies. This review describes a framework for completing second-order statistics of turbulent flows using models based on the Navier–Stokes equations linearized around the turbulent mean velocity. Dynamical couplings between states of the linearized model dictate structural constraints on the statistics of flow fluctuations. Colored-in-time stochastic forcing that drives the linearized model is then sought to account for and reconcile dynamics with available data (that is, partially known statistics). The number of dynamical degrees of freedom that are directly affected by stochastic excitation is minimized as a measure of model parsimony. The spectral content of the resulting colored-in-time stochastic contribution can alternatively arise from a low-rank structural perturbation of the linearized dynamical generator, pointing to suitable dynamical corrections that may account for the absence of the nonlinear interactions in the linearized model.

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.

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