scholarly journals Modulation of the velocity gradient tensor by concurrent large-scale velocity fluctuations in a turbulent mixing layer

2015 ◽  
Vol 777 ◽  
Author(s):  
O. R. H. Buxton
Keyword(s):  
Velocity Gradient ◽  
Turbulent Mixing ◽  
Large Scale ◽  
Mixing Layer ◽  
Small Scale ◽  
Velocity Fluctuations ◽  
Turbulent Mixing Layer ◽  
Local Maxima ◽  
Leibler Divergence ◽  
Small Scales

The modulation of small-scale velocity and velocity gradient quantities by concurrent large-scale velocity fluctuations is observed by consideration of the Kullback–Leibler divergence. This is a measure that quantifies the loss of information in modelling a statistical distribution of small-scale quantities conditioned on concurrent positive large-scale fluctuations by that conditioned on negative large-scale fluctuations. It is observed that the small-scale turbulence is appreciably ‘rougher’ when the concurrent large-scale fluctuation is positive in the low-speed side of a fully developed turbulent mixing layer, which gives further evidence to the convective scale modulation argument of Buxton & Ganapathisubramani (Phys. Fluids, vol. 26, 2014, 125106, 1–19). The definition of the small scales is varied, and regardless of whether the small-scale fluctuations are dominated by dissipation or have the characteristic features of inertial range turbulence they are shown to be modulated by the concurrent large-scale fluctuations. The modulation is observed to persist even when there is a large gap in wavenumber space between the small and large scales, although local maxima are observed at intermediate length scales that are significantly larger than the predefined small scales. Finally, it is observed that the modulation of small-scale dissipation is greater than that for enstrophy with the modulation of the vortex stretching term, indicative of the interaction between strain rate and rotation, being intermediate between the two.

Scale interactions in a mixing layer – the role of the large-scale gradients

2016 ◽  
Vol 791 ◽  
pp. 154-173 ◽  
Author(s):  
D. Fiscaletti ◽  
A. Attili ◽  
F. Bisetti ◽  
G. E. Elsinga
Keyword(s):  
Reynolds Number ◽  
High Speed ◽  
Large Scale ◽  
Mixing Layer ◽  
Physical Space ◽  
Small Scale ◽  
Velocity Fluctuations ◽  
Small Scales ◽  
Low Pass ◽  
Scale Characteristics

The interaction between the large and the small scales of turbulence is investigated in a mixing layer, at a Reynolds number based on the Taylor microscale ($Re_{{\it\lambda}}$) of $250$, via direct numerical simulations. The analysis is performed in physical space, and the local vorticity root-mean-square (r.m.s.) is taken as a measure of the small-scale activity. It is found that positive large-scale velocity fluctuations correspond to large vorticity r.m.s. on the low-speed side of the mixing layer, whereas, they correspond to low vorticity r.m.s. on the high-speed side. The relationship between large and small scales thus depends on position if the vorticity r.m.s. is correlated with the large-scale velocity fluctuations. On the contrary, the correlation coefficient is nearly constant throughout the mixing layer and close to unity if the vorticity r.m.s. is correlated with the large-scale velocity gradients. Therefore, the small-scale activity appears closely related to large-scale gradients, while the correlation between the small-scale activity and the large-scale velocity fluctuations is shown to reflect a property of the large scales. Furthermore, the vorticity from unfiltered (small scales) and from low pass filtered (large scales) velocity fields tend to be aligned when examined within vortical tubes. These results provide evidence for the so-called ‘scale invariance’ (Meneveau & Katz, Annu. Rev. Fluid Mech., vol. 32, 2000, pp. 1–32), and suggest that some of the large-scale characteristics are not lost at the small scales, at least at the Reynolds number achieved in the present simulation.

Large-scale structures in a forced turbulent mixing layer

1985 ◽  
Vol 150 ◽  
pp. 23-39 ◽  
Author(s):  
M. Gaster ◽  
E. Kit ◽  
I. Wygnanski
Keyword(s):  
Turbulent Mixing ◽  
Large Scale ◽  
Phase Distribution ◽  
Mixing Layer ◽  
Global Scale ◽  
Travelling Wave ◽  
Mean Flow ◽  
Turbulent Mixing Layer ◽  
Large Scale Structures ◽  
Scale Structures

The large-scale structures that occur in a forced turbulent mixing layer at moderately high Reynolds numbers have been modelled by linear inviscid stability theory incorporating first-order corrections for slow spatial variations of the mean flow. The perturbation stream function for a spatially growing time-periodic travelling wave has been numerically evaluated for the measured linearly diverging mean flow. In an accompanying experiment periodic oscillations were imposed on the turbulent mixing layer by the motion of a small flap at the trailing edge of the splitter plate that separated the two uniform streams of different velocity. The results of the numerical computations are compared with experimental measurements.When the comparison between experimental data and the computational model was made on a purely local basis, agreement in both the amplitude and phase distribution across the mixing layer was excellent. Comparisons on a global scale revealed, not unexpectedly, less good accuracy in predicting the overall amplification.

Large-scale clustering of coherent fine-scale eddies in a turbulent mixing layer

2018 ◽  
Vol 72 ◽  
pp. 100-108
Author(s):  
Toshitaka Itoh ◽  
Yoshitsugu Naka ◽  
Yuki Minamoto ◽  
Masayasu Shimura ◽  
Mamoru Tanahashi
Keyword(s):  
Turbulent Mixing ◽  
Large Scale ◽  
Mixing Layer ◽  
Fine Scale ◽  
Turbulent Mixing Layer

Vorticity and mixing in Rayleigh–Taylor Boussinesq turbulence

2016 ◽  
Vol 802 ◽  
pp. 395-436 ◽  
Author(s):  
Nicolas Schneider ◽  
Serge Gauthier
Keyword(s):  
Large Scale ◽  
Mixing Layer ◽  
Boussinesq Approximation ◽  
The Self ◽  
Small Scale ◽  
Nonlinear Growth ◽  
Small Scales ◽  
Self Similar ◽  
Order Quantities ◽  
Non Gaussian

The Rayleigh–Taylor instability induced turbulence is studied under the Boussinesq approximation focusing on vorticity and mixing. A direct numerical simulation has been carried out with an auto-adaptive multidomain Chebyshev–Fourier–Fourier numerical method. The spatial resolution is increased up to $(24\times 40)\times 940^{2}=848\,M$ collocation points. The Taylor Reynolds number is $\mathit{Re}_{\unicode[STIX]{x1D706}_{zz}}\approx 142$ and a short inertial range is observed. The nonlinear growth rate of the turbulent mixing layer is found to be close to $\unicode[STIX]{x1D6FC}_{b}=0.021$. Our conclusions may be summarized as follows.(i) The simulation data are in agreement with the scalings for the pressure ($k^{-7/3}$) and the vertical mass flux ($k^{-7/3}$).(ii) Mean quantities have a self-similar behaviour, but some inhomogeneity is still present. For higher-order quantities the self-similar regime is not fully achieved.(iii) In the self-similar regime, the mean dissipation rate and the enstrophy behave as $\langle \overline{\unicode[STIX]{x1D700}}\rangle \propto t$ and $\langle \overline{\unicode[STIX]{x1D714}_{i}\,\unicode[STIX]{x1D714}_{i}}^{1/2}\rangle \propto t^{1/2}$, respectively.(iv) The large-scale velocity fluctuation probability density function (PDF) is Gaussian, while vorticity and dissipation PDFs show large departures from Gaussianity.(v) The pressure PDF exhibits strong departures from Gaussianity and is skewed. This is related to vortex coherent structures.(vi) The intermediate scales of the mixing are isotropic, while small scales remain anisotropic. This leaves open the possibility of a small-scale buoyancy. Velocity intermediate scales are also isotropic, while small scales remain anisotropic. Mixing and dynamics are therefore consistent.(vii) Properties and behaviours of vorticity and enstrophy are detailed. In particular, equations for these quantities are written down under the Boussinesq approximation.(viii) The concentration PDF is quasi-Gaussian. The vertical concentration gradient is both non-Gaussian and strongly skewed.

A ‘turbulent spot’ in an axisymmetric free shear layer. Part 2

1980 ◽  
Vol 98 (1) ◽  
pp. 97-135 ◽  
Author(s):  
A. K. M. F. Hussain ◽  
S. J. Kleis ◽  
M. Sokolov
Keyword(s):  
Time Series ◽  
Reynolds Stress ◽  
Coherent Structure ◽  
Turbulent Mixing ◽  
Large Scale ◽  
Mixing Layer ◽  
Turbulent Mixing Layer ◽  
Phase Average ◽  
Background Turbulence ◽  
Stream Functions

The mechanics of a spark-induced coherent structure (called a ‘spot’) in the turbulent mixing layer of a 12.7 cm diameter incompressible air jet has been investigated through phase-locked measurements at three streamwise stations. Phase averages have been obtained from 200 realizations of X-wire (time-series) data after these are optimally time-aligned with respect to one another through an iterative process of maximization of cross-correlation of individual realizations with the ensemble average. Realizations that are grossly out of alignment owing to turbulence-induced distortions have been rejected; the rejection ratio increases with increasing radial position. Data include phase-average time series of background turbulence intensities, coherent and background Reynolds stresses, vorticity and intermittency at different transverse positions. Spatial distributions of these properties over the extent of the spot have been presented as contour maps. The computed pseudo-stream-functions have been compared with the phase-average streamlines inferred from the measured distributions of the velocity vector. Comparison with the phase-average intermittency contours show that the pseudo-stream-functions are reliable and, even though the integration involved produces smoothed-out stream functions, are most useful in deducing the structure dynamics and its convection velocity.The spark-induced spot is an elongated large-scale coherent vortical structure spanning the entire thickness of the mixing layer, which moves downstream at a convection velocity of about 0.68Ue. The dynamics of the turbulent mixing layer spot, whose signature is buried in the large-amplitude background fluctuations, is much more complicated than that of the boundary-layer spot. The spot transports jet-core fluid outwards at its front and entrains ambient fluid primarily at its back; the outward-momentum transport dominates the inward transport. The Reynolds stress contribution by the spot structure is noticeably larger than that due to the background turbulence. The coherent structure vorticity is significantly modified by the structure-induced organization of the background Reynolds stress at the locations of ‘saddle points’ of the latter's distribution. The vorticity, intermittency and other turbulence measures, zone averaged over the extent of the spot, compare well with the time-average values, thus suggesting that the spark-induced ‘spot’ is probably not different from a naturally occurring large-scale coherent structure.

Local flow topology and velocity gradient invariants in compressible turbulent mixing layer

2015 ◽  
Vol 774 ◽  
pp. 67-94 ◽  
Author(s):  
Navid S. Vaghefi ◽  
Cyrus K. Madnia
Keyword(s):  
Velocity Gradient ◽  
Turbulent Mixing ◽  
Probability Distributions ◽  
Mixing Layer ◽  
Contraction Rate ◽  
Flow Topology ◽  
Gradient Tensor ◽  
Local Flow ◽  
Turbulent Mixing Layer ◽  
Turbulent Region

The local flow topology is studied using the invariants of the velocity gradient tensor in compressible turbulent mixing layer via direct numerical simulation (DNS) data. The topological and dissipating behaviours of the flow are analysed in two different regions: in proximity of the turbulent/non-turbulent interface (TNTI), and inside the turbulent region. It is found that the distribution of various flow topologies in regions close to the TNTI differs from inside the turbulent region, and in these regions the most probable topologies are non-focal. In order to better understand the behaviour of different flow topologies, the probability distributions of vorticity norm, dissipation and rate of stretching are analysed in incompressible, compressed and expanded regions. It is found that the structures undergoing compression–expansion in axial–radial directions have the highest contraction rate in locally compressed regions, and in locally expanded regions the structures undergoing expansion–compression in axial–radial directions have the highest stretching rate. The occurrence probability of different flow topologies conditioned by the dilatation level is presented and it is shown that the structures in the locally compressed regions tend to have stable topologies while in locally expanded regions the unstable topologies are prevalent.

Experimental 3D Analysis of the Large Scale Behaviour of a Plane Turbulent Mixing Layer

2005 ◽  
Vol 74 (2) ◽  
pp. 207-233 ◽  
Author(s):  
Philippe Druault ◽  
Joël Delville ◽  
Jean-paul Bonnet
Keyword(s):  
Turbulent Mixing ◽  
Large Scale ◽  
Mixing Layer ◽  
3D Analysis ◽  
Turbulent Mixing Layer

A Model of Coherent Disturbances in Compressible Mixing Layers

2002 ◽  
Author(s):  
Hong Yang ◽  
Anatoli Tumin
Keyword(s):  
Turbulent Mixing ◽  
Large Scale ◽  
Eddy Viscosity ◽  
Mixing Layer ◽  
Governing Equations ◽  
Turbulent Mixing Layer ◽  
Eddy Viscosity Model ◽  
Temperature And Pressure ◽  
Mean Time ◽  
Theoretical Results

A theoretical model of harmonic perturbations in a compressible turbulent mixing layer is proposed. The model is based on the triple decomposition method. It is assumed that the instantaneous velocities, temperature, and pressure consist of three distinctive components: mean (time-averaged), coherent (phase-averaged), and random (turbulent) motion. The interaction between incoherent turbulent fluctuations and large-scale coherent disturbances is incorporated by the Newtonian eddy viscosity model. The governing equations for the coherent disturbances have the same form as in laminar flow with substitution of the Reynolds number and the Prandtl number by their turbulent counterparts. A slight divergence of the flow is also taken into account. Theoretical results and comparison with experimental data reveal the significance of interaction between the coherent and random constituents of the flow.

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