Complete self-preservation on the axis of a turbulent round jet

2016 ◽  
Vol 790 ◽  
pp. 57-70 ◽  
Author(s):  
L. Djenidi ◽  
R. A. Antonia ◽  
N. Lefeuvre ◽  
J. Lemay
Keyword(s):  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Energy Budget ◽  
Dissipation Rate ◽  
Longitudinal Velocity ◽  
Order Structure ◽  
Mean Velocity ◽  
Round Jet ◽  
The Mean

Self-preservation (SP) solutions on the axis of a turbulent round jet are derived for the transport equation of the second-order structure function of the turbulent kinetic energy ($k$), which may be interpreted as a scale-by-scale (s.b.s.) energy budget. The analysis shows that the mean turbulent energy dissipation rate, $\overline{{\it\epsilon}}$, evolves like $x^{-4}$ ($x$ is the streamwise direction). It is important to stress that this derivation does not use the constancy of the non-dimensional dissipation rate parameter $C_{{\it\epsilon}}=\overline{{\it\epsilon}}u^{\prime 3}/L_{u}$ ($L_{u}$ and $u^{\prime }$ are the integral length scale and root mean square of the longitudinal velocity fluctuation respectively). We show, in fact, that the constancy of $C_{{\it\epsilon}}$ is simply a consequence of complete SP (i.e. SP at all scales of motion). The significance of the analysis relates to the fact that the SP requirements for the mean velocity and mean turbulent kinetic energy (i.e. $U\sim x^{-1}$ and $k\sim x^{-2}$ respectively) are derived without invoking the transport equations for $U$ and $k$. Experimental hot-wire data along the axis of a turbulent round jet show that, after a transient downstream distance which increases with Reynolds number, the turbulence statistics comply with complete SP. For example, the measured $\overline{{\it\epsilon}}$ agrees well with the SP prediction, i.e. $\overline{{\it\epsilon}}\sim x^{-4}$, while the Taylor microscale Reynolds number $Re_{{\it\lambda}}$ remains constant. The analytical expression for the prefactor $A_{{\it\epsilon}}$ for $\overline{{\it\epsilon}}\sim (x-x_{o})^{-4}$ (where $x_{o}$ is a virtual origin), first developed by Thiesset et al. (J. Fluid Mech., vol. 748, 2014, R2) and rederived here solely from the SP analysis of the s.b.s. energy budget, is validated and provides a relatively simple and accurate method for estimating $\overline{{\it\epsilon}}$ along the axis of a turbulent round jet.

The influence of shear-dependent rheology on turbulent pipe flow

2017 ◽  
Vol 822 ◽  
pp. 848-879 ◽  
Author(s):  
J. Singh ◽  
M. Rudman ◽  
H. M. Blackburn
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Energy Budget ◽  
Shear Thinning ◽  
Turbulent Pipe Flow ◽  
Turbulent Kinetic Energy Budget ◽  
Mean Velocity ◽  
Kinetic Energy Budget ◽  
Power Law Fluids ◽  
The Mean

Direct numerical simulations of turbulent pipe flow of power-law fluids at $Re_{\unicode[STIX]{x1D70F}}=323$ are analysed in order to understand the way in which shear thinning or thickening affects first- and second-order flow statistics including turbulent kinetic energy production, transport and dissipation in such flows. The results show that with shear thinning, near-wall streaks become weaker and the axial and azimuthal correlation lengths of axial velocity fluctuations increase. Viscosity fluctuations give rise to an additional shear stress term in the mean momentum equation which is negative for shear-thinning fluids and which increases in magnitude as the fluid becomes more shear thinning: for an equal mean wall shear stress, this term increases the mean velocity gradient in shear-thinning fluids when compared to a Newtonian fluid. Consequently, the mean velocity profile in power-law fluids deviates from the law of the wall $U_{z}^{+}=y^{+}$ in the viscous sublayer when traditional near-wall scaling is used. Consideration is briefly given to an alternative scaling that allows the law of wall to be recovered but which results in loss of a common mean stress profile. With shear thinning, the mean viscosity increases slightly at the wall and its profile appears to be approximately logarithmic in the velocity log layer. Through analysis of the turbulent kinetic energy budget, undertaken here for the first time for generalised Newtonian fluids, it is shown that shear thinning decreases the overall turbulent kinetic energy production but widens the wall-normal region where it is generated. Additional dissipation terms in the mean flow and turbulent kinetic energy budget equations arise from viscosity fluctuations; with shear thinning, these result in a net decrease in the total viscous dissipation. The overall effect of shear thinning on the turbulent kinetic energy budget is found to be largely confined to the inner layers, $y^{+}\lesssim 60$.

On the normalized dissipation parameter in decaying turbulence

2017 ◽  
Vol 817 ◽  
pp. 61-79 ◽  
Author(s):  
L. Djenidi ◽  
N. Lefeuvre ◽  
M. Kamruzzaman ◽  
R. A. Antonia
Keyword(s):  
Reynolds Number ◽  
Energy Dissipation ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Dissipation Rate ◽  
Energy Dissipation Rate ◽  
Grid Turbulence ◽  
Far Field ◽  
Round Jet ◽  
Decaying Turbulence

The Reynolds number dependence of the non-dimensional mean turbulent kinetic energy dissipation rate$C_{\unicode[STIX]{x1D716}}=\overline{\unicode[STIX]{x1D716}}L/u^{\prime 3}$(where$\unicode[STIX]{x1D716}$is the mean turbulent kinetic energy dissipation rate,$L$is an integral length scale and$u^{\prime }$is the velocity root-mean-square) is investigated in decaying turbulence. Expressions for$C_{\unicode[STIX]{x1D716}}$in homogeneous isotropic turbulent (HIT), as approximated by grid turbulence, and in local HIT, as on the axis of the far field of a turbulent round jet, are developed from the Navier–Stokes equations within the framework of a scale-by-scale energy budget. The analysis shows that when turbulence decays/evolves in compliance with self-preservation (SP),$C_{\unicode[STIX]{x1D716}}$remains constant for a given flow condition, e.g. a given initial Reynolds number. Measurements in grid turbulence, which does not satisfy SP, and on the axis in the far field of a round jet, which does comply with SP, show that$C_{\unicode[STIX]{x1D716}}$decreases in the former case and remains constant in the latter, thus supporting the theoretical results. Further, while$C_{\unicode[STIX]{x1D716}}$can remain constant during the decay for a given initial Reynolds number, both the theory and measurements show that it decreases towards a constant,$C_{\unicode[STIX]{x1D716},\infty }$, as$Re_{\unicode[STIX]{x1D706}}$increases. This trend, in agreement with existing data, is not inconsistent with the possibility that$C_{\unicode[STIX]{x1D716}}$tends to a universal constant.

NUMERICAL RESEARCH ON THE EFFECT OF FIBERS ON THE PROPERTY OF TURBULENT FIBER SUSPENSION IN A CHANNEL

2009 ◽  
Vol 23 (03) ◽  
pp. 509-512 ◽  
Author(s):  
SUHUA SHEN ◽  
JIANZHONG LIN
Keyword(s):  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Channel Flow ◽  
Turbulent Channel Flow ◽  
Fiber Suspension ◽  
Additional Stress ◽  
Mean Velocity ◽  
Navier Stokes Equation ◽  
Fiber Concentration

To explore the rheological property in turbulent channel flow of fiber suspensions, the equation of probability distribution function for mean fiber orientation and the Reynolds averaged Navier-Stokes equation with the term of additional stress resulted from fibers were solved with numerical methods to get the distributions of the mean velocity and turbulent kinetic energy. The simulation results show that the effect of fibers on turbulent channel flow is equivalent to an additional viscosity. The turbulent velocity profiles of fiber suspension become gradually sharper by increasing the fiber concentration and/or decreasing the Reynolds number. The turbulent kinetic energy will increase with increasing Reynolds number and fiber concentration.

scholarly journals The streamwise turbulence intensity in the intermediate layer of turbulent pipe flow

2015 ◽  
Vol 774 ◽  
pp. 324-341 ◽  
Author(s):  
J. C. Vassilicos ◽  
J.-P. Laval ◽  
J.-M. Foucaut ◽  
M. Stanislas
Keyword(s):  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Intermediate Layer ◽  
High Reynolds Number ◽  
Logarithmic Derivative ◽  
Turbulent Pipe Flow ◽  
Mean Flow ◽  
The Mean ◽  
High Reynolds

The spectral model of Perryet al. (J. Fluid Mech., vol. 165, 1986, pp. 163–199) predicts that the integral length scale varies very slowly with distance to the wall in the intermediate layer. The only way for the integral length scale’s variation to be more realistic while keeping with the Townsend–Perry attached eddy spectrum is to add a new wavenumber range to the model at wavenumbers smaller than that spectrum. This necessary addition can also account for the high-Reynolds-number outer peak of the turbulent kinetic energy in the intermediate layer. An analytic expression is obtained for this outer peak in agreement with extremely high-Reynolds-number data by Hultmarket al. (Phys. Rev. Lett., vol. 108, 2012, 094501;J. Fluid Mech., vol. 728, 2013, pp. 376–395). Townsend’s (The Structure of Turbulent Shear Flows, 1976, Cambridge University Press) production–dissipation balance and the finding of Dallaset al. (Phys. Rev. E, vol. 80, 2009, 046306) that, in the intermediate layer, the eddy turnover time scales with skin friction velocity and distance to the wall implies that the logarithmic derivative of the mean flow has an outer peak at the same location as the turbulent kinetic energy. This is seen in the data of Hultmarket al. (Phys. Rev. Lett., vol. 108, 2012, 094501;J. Fluid Mech., vol. 728, 2013, pp. 376–395). The same approach also predicts that the logarithmic derivative of the mean flow has a logarithmic decay at distances to the wall larger than the position of the outer peak. This qualitative prediction is also supported by the aforementioned data.

Simulation of a propelled wake with moderate excess momentum in a stratified fluid

2011 ◽  
Vol 692 ◽  
pp. 28-52 ◽  
Author(s):  
Matthew B. de Stadler ◽  
Sutanu Sarkar
Keyword(s):  
Kinetic Energy ◽  
Velocity Profile ◽  
Turbulent Kinetic Energy ◽  
Vertical Direction ◽  
Qualitative Change ◽  
Stratified Fluid ◽  
Mean Velocity ◽  
Moderate Amount ◽  
Excess Momentum ◽  
The Mean

AbstractDirect numerical simulation is used to simulate the turbulent wake behind an accelerating axisymmetric self-propelled body in a stratified fluid. Acceleration is modelled by adding a velocity profile corresponding to net thrust to a self-propelled velocity profile resulting in a wake with excess momentum. The effect of a small to moderate amount of excess momentum on the initially momentumless self-propelled wake is investigated to evaluate if the addition of excess momentum leads to a large qualitative change in wake dynamics. Both the amount and shape of excess momentum are varied. Increasing the amount of excess momentum and/or decreasing the radial extent of excess momentum was found to increase the defect velocity, mean kinetic energy, shear in the velocity gradient and the wake width. The increased shear in the mean profile resulted in increased production of turbulent kinetic energy leading to an increase in turbulent kinetic energy and its dissipation. Slightly larger vorticity structures were observed in the late wake with excess momentum although the differences between vorticity structures in the self-propelled and 40 % excess momentum cases was significantly smaller than suggested by previous experiments. Buoyancy was found to preserve the doubly inflected velocity profile in the vertical direction, and similarity for the mean velocity and turbulent kinetic energy was found to occur in both horizontal and vertical directions. While quantitative differences were observed between cases with and without excess momentum, qualitatively similar evolution was found to occur.

Measurements of Losses and Reynolds Stresses in the Secondary Flow Downstream of a Low-Speed Linear Turbine Cascade

2010 ◽  
Author(s):  
G. D. MacIsaac ◽  
S. A. Sjolander ◽  
T. J. Praisner
Keyword(s):  
Kinetic Energy ◽  
Turbulent Flow ◽  
Secondary Flow ◽  
Turbulent Kinetic Energy ◽  
Pressure Probe ◽  
Turbine Cascade ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Hole Pressure ◽  
The Mean

Experimental measurements of the mean and turbulent flow field were preformed downstream of a low-speed linear turbine cascade. The influence of turbulence on the production of secondary losses is examined. Steady pressure measurements were collected using a seven-hole pressure probe and the turbulent flow quantities were measured using a rotatable x-type hotwire probe. Each probe was traversed downstream of the cascade along planes positioned at three axial locations: 100%, 120% and 140% of the axial chord (Cx) downstream of the leading edge. The seven-hole pressure probe was used to determine the local total and static pressure as well as the three mean velocity components. The rotatable x-type hotwire probe, in addition to the mean velocity components, provided the local Reynolds stresses and the turbulent kinetic energy. The axial development of the secondary losses is examined in relation to the rate at which mean kinetic energy is transferred to turbulent kinetic energy. In general, losses are generated as a result of the mean flow dissipating kinetic energy through the action of viscosity. The production of turbulence can be considered a preliminary step in this process. The measured total pressure contours from the three axial locations (1.00, 1.20 and 1.40Cx) demonstrate the development of the secondary losses. The peak loss core in each plane consists mainly of low momentum fluid that originates from the inlet endwall boundary layer. There are, however, additional losses generated as the flow mixes with downstream distance. These losses have been found to relate to the turbulent Reynolds stresses. An examination of the turbulent deformation work term demonstrates a mechanism of loss generation in the secondary flow region. The importance of the Reynolds shear stress to this process is explored in detail.

scholarly journals Consequences of self-preservation on the axis of a turbulent round jet

2014 ◽  
Vol 748 ◽  
Author(s):  
F. Thiesset ◽  
R. A. Antonia ◽  
L. Djenidi
Keyword(s):  
Large Scale ◽  
Transverse Velocity ◽  
Longitudinal Velocity ◽  
Asymptotic State ◽  
Mean Velocity ◽  
Exact Relation ◽  
Round Jet ◽  
Velocity Variance ◽  
The Mean ◽  
Decaying Turbulence

AbstractOn the basis of a two-point similarity analysis, the well-known power-law variations for the mean kinetic energy dissipation rate $\overline{\epsilon }$ and the longitudinal velocity variance $\overline{u^2}$ on the axis of a round jet are derived. In particular, the prefactor for $\overline{\epsilon } \propto (x-x_0)^{-4}$, where $x_0$ is a virtual origin, follows immediately from the variation of the mean velocity, the constancy of the local turbulent intensity and the ratio between the axial and transverse velocity variance. Second, the limit at small separations of the two-point budget equation yields an exact relation illustrating the equilibrium between the skewness of the longitudinal velocity derivative $S$ and the destruction coefficient $G$ of enstrophy. By comparing the latter relation with that for homogeneous isotropic decaying turbulence, it is shown that the approach towards the asymptotic state at infinite Reynolds number of $S+2G/R_{\lambda }$ in the jet differs from that in purely decaying turbulence, although $S+2G/R_{\lambda } \propto R_{\lambda }^{-1}$ in each case. This suggests that, at finite Reynolds numbers, the transport equation for $\overline{\epsilon }$ imposes a fundamental constraint on the balance between $S$ and $G$ that depends on the type of large-scale forcing and may thus differ from flow to flow. This questions the conjecture that $S$ and $G$ follow a universal evolution with $R_{\lambda }$; instead, $S$ and $G$ must be tested separately in each flow. The implication for the constant $C_{\epsilon 2}$ in the $k-\overline{\epsilon }$ model is also discussed.

Experimental Study of Reynolds Number Effects on Three-Dimensional Offset Jets

2014 ◽  
Author(s):  
Zacharie M. J. Durand ◽  
Shawn P. Clark ◽  
Mark F. Tachie ◽  
Jarrod Malenchak ◽  
Getnet Muluye
Keyword(s):  
Experimental Study ◽  
Reynolds Number ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Reynolds Shear Stress ◽  
Three Dimensional ◽  
Shear Stresses ◽  
Mean Velocity ◽  
Flow Measurements ◽  
Reynolds Number Effects

The effect of Reynolds number on three-dimensional offset jets was investigated in this study. An acoustic Doppler velocimeter simultaneously measured all three components of velocity, U, V and W, and turbulence intensity, urms, vrms, and wrms, and all three Reynolds shear stresses, uv, uw, and vw. Turbulent kinetic energy, k, was calculated with all three values of turbulence intensities. Flow measurements were performed at Reynolds numbers of 34,000, 53,000 and 86,000. Results of this experimental study indicate the wall-normal location of maximum mean velocity and jet spread to be independent of Reynolds number. The effects on maximum mean velocity decay are reduced with increasing Reynolds number. Profiles of mean velocities, U, V and W, turbulence intensities, urms, vrms, and wrms, and turbulent kinetic energy, k, show independence of Reynolds number. Reynolds shear stress uv was independent of Reynolds number while the magnitude of uw was reduced at higher Reynolds number.

Turbulent Energy Budget in a Tip Leakage Flow: A Comparison Between RANS and LES

2017 ◽  
Author(s):  
Jean-François Monier ◽  
Jérôme Boudet ◽  
Joëlle Caro ◽  
Liang Shao
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Constitutive Relation ◽  
Energy Budget ◽  
Reynolds Stresses ◽  
Turbulent Kinetic Energy Budget ◽  
Potential Core ◽  
Kinetic Energy Budget ◽  
The Mean ◽  
Rans Simulations

An academic configuration of a single airfoil and a flat casing with clearance, put in the potential core of a jet at Rec = 9.3 × 105, is studied in order to analyse the turbulence modelling. A zonal large-eddy simulation (ZLES), validated against experimental results, is considered as a reference to evaluate two steady Reynolds-averaged Navier-Stokes (RANS) simulations. Both RANS simulations use the original Wilcox k-ω model. They differ on the constitutive relation: one uses the classical Boussinesq constitutive relation, while the other relies on the quadratic constitutive relation (QCR). The analysis focuses on the mean velocities, the Reynolds stresses and a term-to-term decomposition of the turbulent kinetic energy budget on a plane through the clearance. RANS represents quite well the mean velocities, but under-estimates the Reynolds stresses, thus under-estimates every turbulent kinetic energy budget term. The QCR has little effect on the flow and the turbulent quantities. The method allowed a fine analysis of the physics of the turbulence.

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