Turbulent Kinetic Energy Evolution in the Near Field of a Rotating-Pipe Round Jet

2017 ◽  
pp. 553-558
Author(s):  
R. Mullyadzhanov ◽  
S. Abdurakipov ◽  
K. Hanjalić
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Near Field ◽  
Energy Evolution ◽  
Round Jet

Turbulent Jet Mixing Enhancement and Control Using Self-Excited Nozzles

2007 ◽  
Vol 129 (7) ◽  
pp. 842-851 ◽  
Author(s):  
Uri Vandsburger ◽  
Yiqing Yuan
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Nozzle Exit ◽  
Large Scale ◽  
Rectangular Cross Section ◽  
Near Field ◽  
Excitation Frequency ◽  
Mixing Enhancement ◽  
Mixing Rate ◽  
Jet Mixing

A new self-excited jet methodology was developed for the mixing enhancement of jet fluid with its surrounding, quiescent, stagnant, or coflowing fluid. The nozzles, of a square or rectangular cross section, featured two flexible side walls that could go into aerodynamically-induced vibration. The mixing of nozzle fluid was measured using planar laser-induced fluorescence (PLIF) from acetone seeded into the nozzle fluid. Overall, the self-excited jet showed enhanced mixing with the ambient fluid; for example, at 390Hz excitation a mixing rate enhancement of 400% at x∕D=4 and 200% at x∕D=20 over the unexcited jet. The mixing rate was sensitive to the excitation frequency, increasing by 60% with the frequency changing from 200 to 390Hz (corresponding to a Strouhal number from 0.052 to 0.1). It was also observed that the mixing rate increased with the coflow velocity. To explain the observed mixing enhancement, the flow field was studied in detail using four-element hot wire probes. This led to the observation of two pairs of counter rotating large-scale streamwise vortices as the dominant structures in the excited flow. Shedding right from the nozzle exit, these inviscid vortices provided a rapid transport of the momentum and mass between the jet and the surrounding fluid at a length scale comparable to half-nozzle diameter. Moreover, the excited jet gained as much as six times the turbulent kinetic energy at the nozzle exit over the unexcited jet. Most of the turbulent kinetic energy is concentrated within five diameters from the nozzle exit, distributed across the entire jet width, explaining the increased mixing in the near field.

Controlling Turbulence in a Rearward-Facing Step Combustor Using Countercurrent Shear

2005 ◽  
Vol 127 (3) ◽  
pp. 438-448 ◽  
Author(s):  
David J. Forliti ◽  
Paul J. Strykowski
Keyword(s):  
Kinetic Energy ◽  
Shear Flow ◽  
Shear Layer ◽  
Turbulent Kinetic Energy ◽  
Near Field ◽  
Sudden Expansion ◽  
Turbulent Fluctuation ◽  
Separated Shear Layer ◽  
Field Control ◽  
Countercurrent Shear

The present work describes the application of countercurrent shear flow control to the nonreacting flow in a novel step combustor. The countercurrent shear control employs a suction based approach, which induces counterflow through a gap at the sudden expansion plane. Peak turbulent fluctuation levels, cross-stream averaged turbulent kinetic energy, and cross-stream momentum diffusion increased with applied suction. The control downstream of the step operates via two mechanisms: enhanced global recirculation and near field control of the separated shear layer. The use of counterflow also enhances three dimensionality, a feature that is expected to be beneficial under burning conditions.

Budgets of turbulent kinetic energy, Reynolds stresses, variance of temperature fluctuations and turbulent heat fluxes in a round jet

2015 ◽  
Vol 774 ◽  
pp. 95-142 ◽  
Author(s):  
Alexis Darisse ◽  
Jean Lemay ◽  
Azemi Benaïssa
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Laser Doppler Velocimetry ◽  
Temperature Fluctuations ◽  
Passive Scalar ◽  
Heat Fluxes ◽  
Turbulent Heat ◽  
Doppler Velocimetry ◽  
Round Jet ◽  
Turbulent Heat Fluxes

The self-preserving region of a free round turbulent air jet at high Reynolds number is investigated experimentally (at$x/D=30$,$\mathit{Re}_{D}=1.4\times 10^{5}$and$\mathit{Re}_{{\it\lambda}}=548$). Air is slightly heated ($20\,^{\circ }\text{C}$above ambient) in order to use temperature as a passive scalar. Laser doppler velocimetry and simultaneous laser doppler velocimetry–cold-wire thermometry measurements are used to evaluate turbulent kinetic energy and temperature variance budgets in identical flow conditions. Special attention is paid to the control of initial conditions and the statistical convergence of the data acquired. Measurements of the variance, third-order moments and mixed correlations of velocity and temperature are provided (including$\overline{vw^{2}}$,$\overline{u{\it\theta}^{2}}$,$\overline{v{\it\theta}^{2}}$,$\overline{u^{2}{\it\theta}}$,$\overline{v^{2}{\it\theta}}$and$\overline{uv{\it\theta}}$). The agreement of the present results with the analytical expressions given by the continuity, mean momentum and mean enthalpy equations supports their consistency. The turbulent kinetic energy transport budget is established using Lumley’s model for the pressure diffusion term. Dissipation is inferred as the closing balance. The transport budgets of the$\overline{u_{i}u_{j}}$components are also determined, which enables analysis of the turbulent kinetic energy redistribution mechanisms. The impact of the surrogacy$\overline{vw^{2}}=\overline{v^{3}}$is then analysed in detail. In addition, the present data offer an opportunity to evaluate every single term of the passive scalar transport budget, except for the dissipation, which is also inferred as the closing balance. Hence, estimates of the dissipation rates of turbulent kinetic energy and temperature fluctuations (${\it\epsilon}_{k}$and${\it\epsilon}_{{\it\theta}}$) are proposed here for use in future studies of the passive scalar in a turbulent round jet. Finally, the budgets of turbulent heat fluxes ($\overline{u_{i}{\it\theta}}$) are presented.

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.

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.

Probability law of turbulent kinetic energy in the atmospheric surface layer

2021 ◽  
Vol 6 (7) ◽  
Author(s):  
Mohammad Allouche ◽  
Gabriel G. Katul ◽  
Jose D. Fuentes ◽  
Elie Bou-Zeid
Keyword(s):  
Surface Layer ◽  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Atmospheric Surface Layer

scholarly journals A New Method to Determine the Impact of Individual Field Quantities on Cycle-to-Cycle Variations in a Spark-Ignited Gas Engine

Energies ◽  
2021 ◽  
Vol 14 (14) ◽  
pp. 4136
Author(s):  
Clemens Gößnitzer ◽  
Shawn Givler
Keyword(s):  
Kinetic Energy ◽  
Flow Field ◽  
Turbulent Kinetic Energy ◽  
Negative Impact ◽  
Operating Conditions ◽  
Engine Operation ◽  
Gas Engine ◽  
Cycle Simulation ◽  
Simulation Results ◽  
The Impact

Cycle-to-cycle variations (CCV) in spark-ignited (SI) engines impose performance limitations and in the extreme limit can lead to very strong, potentially damaging cycles. Thus, CCV force sub-optimal engine operating conditions. A deeper understanding of CCV is key to enabling control strategies, improving engine design and reducing the negative impact of CCV on engine operation. This paper presents a new simulation strategy which allows investigation of the impact of individual physical quantities (e.g., flow field or turbulence quantities) on CCV separately. As a first step, multi-cycle unsteady Reynolds-averaged Navier–Stokes (uRANS) computational fluid dynamics (CFD) simulations of a spark-ignited natural gas engine are performed. For each cycle, simulation results just prior to each spark timing are taken. Next, simulation results from different cycles are combined: one quantity, e.g., the flow field, is extracted from a snapshot of one given cycle, and all other quantities are taken from a snapshot from a different cycle. Such a combination yields a new snapshot. With the combined snapshot, the simulation is continued until the end of combustion. The results obtained with combined snapshots show that the velocity field seems to have the highest impact on CCV. Turbulence intensity, quantified by the turbulent kinetic energy and turbulent kinetic energy dissipation rate, has a similar value for all snapshots. Thus, their impact on CCV is small compared to the flow field. This novel methodology is very flexible and allows investigation of the sources of CCV which have been difficult to investigate in the past.

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