Measurement and Simulation of Turbulent Mixing in a Jet in Crossflow

2011 ◽  
Vol 133 (6) ◽  
Author(s):  
Flavio Cesar Cunha Galeazzo ◽  
Georg Donnert ◽  
Peter Habisreuther ◽  
Nikolaos Zarzalis ◽  
Richard J. Valdes ◽  
...  
Keyword(s):  
Turbulence Model ◽  
Turbulent Mixing ◽  
Turbulence Modeling ◽  
Practical Importance ◽  
Navier Stokes ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Jet In Crossflow ◽  
Turbulent Schmidt Number ◽  
Air Mixing

Computational fluid dynamics (CFD) has an important role in current research. While large eddy simulations (LES) are now common practice in academia, Reynolds-averaged Navier–Stokes (RANS) simulations are still very common in the industry. Using RANS allows faster simulations, however, the choice of the turbulence model has a bigger impact on the results. An important influence of the turbulence modeling is the description of turbulent mixing. Experience has shown that often inaccurate simulations of combustion processes originate from an inadequate description of the mixing field. A simple turbulent flow and mixing configuration of major theoretical and practical importance is the jet in crossflow (JIC). Due to its good fuel-air mixing capability over a small distance, JIC is favored by gas turbine manufacturers. As the design of the mixing process is the key to creating stable low NOx combustion systems, reliable predictive tools and detailed understanding of this basic system are still demanded. Therefore, the current study has re-investigated the JIC configuration under engine relevant conditions both experimentally and numerically using the most sophisticated tools available today. The combination of planar particle image velocimetry and laser induced fluorescence was used to measure the turbulent velocity and concentration fields as well as to determine the correlations of the Reynolds stress tensor ui′uj′¯ and the Reynolds flux vector ui′c′¯. Boundary conditions were determined using laser Doppler velocimetry. The comparisons between the measurements and simulation using RANS and LES showed that the mean velocity field was well described using the SST turbulence model. However, the Reynolds stresses and more so, the Reynolds fluxes deviate substantially from the measured data. The systematic variation of the turbulent Schmidt number reveals the limited influence of this parameter indicating that the basic modeling is amiss. The results of the LES simulation using the standard Smagorinsky model were found to provide much better agreement with the experiments also in the description of turbulent mixing.

Measurement and Simulation of Turbulent Mixing in a Jet in Crossflow

2010 ◽  
Author(s):  
Flavio Cesar Cunha Galeazzo ◽  
Georg Donnert ◽  
Peter Habisreuther ◽  
Nikolaos Zarzalis ◽  
Richard J. Valdes ◽  
...  
Keyword(s):  
Turbulence Model ◽  
Turbulent Mixing ◽  
Turbulence Modeling ◽  
Practical Importance ◽  
Navier Stokes ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Jet In Crossflow ◽  
Turbulent Schmidt Number ◽  
Air Mixing

Computational Fluid Dynamics (CFD) has an important role in current research. While Large Eddy Simulations (LES) are now common practice in academia, Reynolds-averaged Navier-Stokes (RANS) simulations are still very common in industry. Using RANS allows faster simulations, however the choice of the turbulence model has a bigger impact on the results. An important influence of the turbulence modeling is the description of turbulent mixing. Experience has shown that often inaccurate simulations of combustion processes originate from an inadequate description of the mixing field. A simple turbulent flow and mixing configuration of major theoretical and practical importance is the jet in crossflow (JIC). Due to its good fuel-air mixing capability over a small distance JIC is favored by gas turbine manufacturers. As the design of the mixing process is the key to creating stable low NOx combustion systems, reliable predictive tools and detailed understanding of this basic system are still demanded. Therefore the current study has re-investigated the JIC configuration under engine relevant conditions both experimentally and numerically using the most sophisticated tools available today. The combination of planar Particle Image Velocimetry (PIV) and Laser Induced Fluorescence (LIF) was used to measure the turbulent velocity and concentration fields as well as to determine the correlations of the Reynolds stress tensor ui′uj′ and the Reynolds flux vector ui′c′. Boundary conditions were determined using Laser Doppler Velocimetry. The comparisons between the measurements and simulation using RANS and LES showed that the mean velocity field was well described using the SST turbulence model. However, the Reynolds stresses and more so the Reynolds fluxes deviate substantially from the measured data. The systematic variation of the turbulent Schmidt number reveals the limited influence of this parameter indicating that the basic modeling is amiss. The results of the LES simulation using the standard Smagorinsky model were found to provide much better agreement with experiments also in the description of turbulent mixing.

Computational Modeling of Turbulent Mixing of a Transverse Jet

2010 ◽  
Vol 133 (2) ◽  
Author(s):  
Elizaveta M. Ivanova ◽  
Berthold E. Noll ◽  
Manfred Aigner
Keyword(s):  
Turbulent Mixing ◽  
Passive Scalar ◽  
Navier Stokes ◽  
Test Case ◽  
Scalar Mixing ◽  
Reynolds Stresses ◽  
Mixing Processes ◽  
Jet In Crossflow ◽  
Turbulent Schmidt Number ◽  
Reynolds Averaged Navier Stokes

This paper presents numerical simulations of turbulent mixing of a jet in crossflow. The test case is chosen to resemble scalar mixing processes in the premixing zones of gas turbine combustion chambers. Steady and unsteady simulations employing three different computational approaches are presented: steady Reynolds-averaged Navier–Stokes, unsteady Reynolds-averaged Navier–Stokes, and scale-adaptive simulations. Presented results comprise the (time-averaged) profiles of flow velocities, turbulent kinetic energy of the flow, Reynolds stresses, passive scalar distribution, turbulent scalar fluxes, and the turbulent variance of the passive scalar. All presented results are directly validated against experimental data. Additionally, two parameter studies are presented. Both studies are related to the accuracy of the turbulent scalar mixing predictions for all used simulation methods. In the first study, the dependence of the scalar mixing predictions on the value of the turbulent Schmidt number is considered. In the second study, the dependence of the predicted turbulent scalar variance on the used modeling approach is analyzed.

Computational Modelling of Turbulent Mixing of a Transverse Jet

2010 ◽  
Author(s):  
Elizaveta Ivanova ◽  
Berthold Noll ◽  
Manfred Aigner
Keyword(s):  
Turbulent Mixing ◽  
Computational Modelling ◽  
Passive Scalar ◽  
Navier Stokes ◽  
Test Case ◽  
Scalar Mixing ◽  
Reynolds Stresses ◽  
Mixing Processes ◽  
Turbulent Schmidt Number ◽  
Reynolds Averaged Navier Stokes

This paper presents numerical simulations of turbulent mixing of a jet in crossflow. The test case is chosen to resemble scalar mixing processes in the premixing zones of gas turbine combustion chambers. Steady and unsteady simulations employing three different computational approaches are presented: steady Reynolds-Averaged Navier-Stokes (RANS), unsteady Reynolds-Averaged Navier-Stokes (URANS), and Scale-Adaptive Simulations (SAS). Presented results comprise the (time-averaged) profiles of flow velocities, turbulent kinetic energy of the flow, Reynolds stresses, passive scalar distribution, turbulent scalar fluxes, and the turbulent variance of the passive scalar. All presented results are directly validated against experimental data. Additionally two parameter studies are presented. Both studies are related to the accuracy of the turbulent scalar mixing predictions for all used simulation methods. In the first study the dependence of the scalar mixing predictions on the value of the turbulent Schmidt number is considered. In the second study the dependence of the predicted turbulent scalar variance on the used modelling approach is analysed.

scholarly journals Three-Dimensional Turbulent Vortex Shedding From a Surface-Mounted Square Cylinder: Predictions With Large-Eddy Simulations and URANS

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
B. A. Younis ◽  
A. Abrishamchi
Keyword(s):  
Experimental Data ◽  
Turbulence Model ◽  
Stokes Equations ◽  
Three Dimensional ◽  
Large Eddy Simulations ◽  
Navier Stokes ◽  
Reynolds Stresses ◽  
Mean Flow ◽  
Navier Stokes Equations ◽  
Large Eddy

The paper reports on the prediction of the turbulent flow field around a three-dimensional, surface mounted, square-sectioned cylinder at Reynolds numbers in the range 104–105. The effects of turbulence are accounted for in two different ways: by performing large-eddy simulations (LES) with a Smagorinsky model for the subgrid-scale motions and by solving the unsteady form of the Reynolds-averaged Navier–Stokes equations (URANS) together with a turbulence model to determine the resulting Reynolds stresses. The turbulence model used is a two-equation, eddy-viscosity closure that incorporates a term designed to account for the interactions between the organized mean-flow periodicity and the random turbulent motions. Comparisons with experimental data show that the two approaches yield results that are generally comparable and in good accord with the experimental data. The main conclusion of this work is that the URANS approach, which is considerably less demanding in terms of computer resources than LES, can reliably be used for the prediction of unsteady separated flows provided that the effects of organized mean-flow unsteadiness on the turbulence are properly accounted for in the turbulence model.

Turbulent Mixing Process of a Round Jet With Slot Lobes

2020 ◽  
Vol 143 (3) ◽  
Author(s):  
Paul J. Kristo ◽  
Coleman D. Hoff ◽  
Ian G. R. Craig ◽  
Mark L. Kimber
Keyword(s):  
Turbulent Mixing ◽  
Near Field ◽  
Streamwise Velocity ◽  
Velocity Profiles ◽  
Separate Flow ◽  
Geometric Feature ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Round Jet ◽  
Turbulent Statistics

Abstract Turbulent mixing in the near region of a round jet with three slot lobes is examined via mean velocity and turbulent statistics and structures at a Reynolds number of 15,000. The design utilizes separate flow motivations upstream of each geometric feature, deviating from conventional nozzles or orifice plates. Immediate outlet velocity profiles are heavily influenced by opposing pressure gradients between the neighboring round and slot streams. Spanwise mean velocity profiles reveal the majority of the convective exchange between a given slot and the round center occurs in the immediate near field, but has lasting effects on the axial centerline profiles downstream. This is also reflected by the velocity half-widths, exhibiting asymmetry across the entirety of available measurements. Centerline turbulence intensities exhibit strong and short-lived isotropy. The increasingly anisotropic intensities found downstream are lower than similar geometries from the literature, implying that mixing development is inhibited. Reynolds stresses at the round-slot interface are significantly smaller than the round-stagnant exchange, but achieve a symmetric condition at x/D ≅ 4. Two-point spatial correlations of the fluctuating streamwise velocity exhibit stronger dependence toward the axial centerline at the round-slot interface in comparison to the nominal round radius. In contrast, spanwise velocity fluctuations exhibit nearly identical, localized behaviors on each side of the jet. Corresponding differences in streamwise integral length scale peak in the range 1.0 ≤ x/D ≤ 1.5, and so too do the turbulent structures in this area, as a result of the collated jet geometry.

Direct simulations of low-Reynolds-number turbulent flow in a rotating channel

1993 ◽  
Vol 256 ◽  
pp. 163-197 ◽  
Author(s):  
Reidar Kristoffersen ◽  
Helge I. Andersson
Keyword(s):  
Reynolds Number ◽  
Turbulent Flow ◽  
Stokes Equations ◽  
Navier Stokes ◽  
Complete Suppression ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Computational Mesh ◽  
Developed Pressure ◽  
Rotating Channel

Direct numerical simulations of fully developed pressure-driven turbulent flow in a rotating channel have been performed. The unsteady Navier–Stokes equations were written for flow in a constantly rotating frame of reference and solved numerically by means of a finite-difference technique on a 128 × 128 × 128 computational mesh. The Reynolds number, based on the bulk mean velocity Um and the channel half-width h, was about 2900, while the rotation number Ro = 2|Ω|h/Um varied from 0 to 0.5. Without system rotation, results of the simulation were in good agreement with the accurate reference simulation of Kim, Moin & Moser (1987) and available experimental data. The simulated flow fields subject to rotation revealed fascinating effects exerted by the Coriolis force on channel flow turbulence. With weak rotation (Ro = 0.01) the turbulence statistics across the channel varied only slightly compared with the nonrotating case, and opposite effects were observed near the pressure and suction sides of the channel. With increasing rotation the augmentation and damping of the turbulence along the pressure and suction sides, respectively, became more significant, resulting in highly asymmetric profiles of mean velocity and turbulent Reynolds stresses. In accordance with the experimental observations of Johnston, Halleen & Lezius (1972), the mean velocity profile exhibited an appreciable region with slope 2Ω. At Ro = 0.50 the Reynolds stresses vanished in the vicinity of the stabilized side, and the nearly complete suppression of the turbulent agitation was confirmed by marker particle trackings and two-point velocity correlations. Rotational-induced Taylor-Görtler-like counter-rotating streamwise vortices have been identified, and the simulations suggest that the vortices are shifted slightly towards the pressure side with increasing rotation rates, and the number of vortex pairs therefore tend to increase with Ro.

Flow in a Mechanical Bileaflet Heart Valve at Laminar and Near-Peak Systole Flow Rates: CFD Simulations and Experiments

2005 ◽  
Vol 127 (5) ◽  
pp. 782-797 ◽  
Author(s):  
Liang Ge ◽  
Hwa-Liang Leo ◽  
Fotis Sotiropoulos ◽  
Ajit P. Yoganathan
Keyword(s):  
Heart Valve ◽  
Turbulence Modeling ◽  
Mechanical Heart Valve ◽  
Reynolds Numbers ◽  
Navier Stokes ◽  
Detached Eddy Simulation ◽  
Cfd Simulations ◽  
Mean Velocity ◽  
Eddy Simulation ◽  
Flow Through

Time-accurate, fully 3D numerical simulations and particle image velocity laboratory experiments are carried out for flow through a fully open bileaflet mechanical heart valve under steady (nonpulsatile) inflow conditions. Flows at two different Reynolds numbers, one in the laminar regime and the other turbulent (near-peak systole flow rate), are investigated. A direct numerical simulation is carried out for the laminar flow case while the turbulent flow is investigated with two different unsteady statistical turbulence modeling approaches, unsteady Reynolds-averaged Navier-Stokes (URANS) and detached-eddy simulation (DES) approach. For both the laminar and turbulent cases the computed mean velocity profiles are in good overall agreement with the measurements. For the turbulent simulations, however, the comparisons with the measurements demonstrate clearly the superiority of the DES approach and underscore its potential as a powerful modeling tool of cardiovascular flows at physiological conditions. The study reveals numerous previously unknown features of the flow.

scholarly journals The Effect of Schmidt Number on Turbulent Scalar Mixing in a Jet-in-Crossflow

1999 ◽  
Author(s):  
Guangbin He ◽  
Yanhu Guo ◽  
Andrew T. Hsu ◽  
A. Brankovic ◽  
S. Syed ◽  
...  
Keyword(s):  
Turbulence Model ◽  
Momentum Flux ◽  
Schmidt Number ◽  
Stokes Equations ◽  
Scalar Fields ◽  
Spreading Rate ◽  
Navier Stokes ◽  
Appreciable Effect ◽  
Jet In Crossflow ◽  
Schmidt Numbers

The adequacy and accuracy of the constant Schmidt number assumption in predicting turbulent scalar fields in jet-in-crossflows are assessed in the present work. A round jet injected into a confined crossflow in a rectangular tunnel has been simulated using the Reynolds-Averaged Navier-Stokes equations coupled with the standard k-ε turbulence model. A semi-analytical qualitative analysis was made to guide the selection of Schmidt number values. A series of parametric studies were performed, and Schmidt numbers ranging from 0.2 to 1.5 and jet-to-crossflow momentum flux ratios from 8 to 72 were tested. The principal observation is that the Schmidt number does not have an appreciable effect on the species penetration, but it does have a significant effect on species spreading rate in jet-in-crossflows, especially for the cases where the jet-to-crossflow momentum flux ratios are relatively small. A Schmidt number of 0.2 is recommended for best agreement with data. The limitations of the standard k–ε turbulence model and the constant Schmidt number assumption are discussed.

A Numerical Study on the Turbulent Schmidt Numbers in a Jet in Crossflow

2012 ◽  
Vol 135 (1) ◽  
Author(s):  
Elizaveta M. Ivanova ◽  
Berthold E. Noll ◽  
Manfred Aigner
Keyword(s):  
Schmidt Number ◽  
Numerical Study ◽  
Scalar Fields ◽  
Navier Stokes ◽  
Rans Model ◽  
Eddy Simulation ◽  
Jet In Crossflow ◽  
Turbulent Schmidt Number ◽  
Optimal Value ◽  
Schmidt Numbers

This work presents a numerical study on the turbulent Schmidt numbers in jets in crossflow. This study contains two main parts. In the first part, the problem of the proper choice of the turbulent Schmidt number in the Reynolds-averaged Navier-Stokes (RANS) jet in crossflow mixing simulations is outlined. The results of RANS employing the shear-stress transport (SST) model of Menter and its curvature correction modification and different turbulent Schmidt number values are validated against experimental data. The dependence of the optimal value of the turbulent Schmidt number on the dynamic RANS model is studied. Furthermore, a comparison is made with the large-eddy simulation (LES) results obtained using the wall-adapted local eddy viscosity (WALE) model. The accuracy given by LES is superior in comparison to RANS results. This leads to the second part of the current study, in which the time-averaged mean and fluctuating velocity and scalar fields from LES are used for the evaluation of the turbulent viscosities, turbulent scalar diffusivities, and the turbulent Schmidt numbers in a jet in crossflow configuration. The values obtained from the LES data are compared with those given by the RANS modeling. The deviations are discussed, and the possible ways for the RANS model improvements are outlined.

A K—ε—γ equation turbulence model

1992 ◽  
Vol 237 ◽  
pp. 301-322 ◽  
Author(s):  
Ji Ryong Cho ◽  
Myung Kyoon Chung
Keyword(s):  
Kinetic Energy ◽  
Turbulent Kinetic Energy ◽  
Turbulence Model ◽  
Mixing Layer ◽  
Spreading Rate ◽  
Reynolds Stresses ◽  
Mean Velocity ◽  
Model Equations ◽  
Entrainment Effect ◽  
Intermittency Factor

By considering the entrainment effect on the intermittency in the free boundary of shear layers, a set of turbulence model equations for the turbulent kinetic energy k, the dissipation rate ε, and the intermittency factor γ is proposed. This enables us to incorporate explicitly the intermittency effect in the conventional K–ε turbulence model equations. The eddy viscosity νt is estimated by a function of K, ε and γ. In contrast to the closure schemes of previous intermittency modelling which employ conditional zone averaged moments, the present model equations are based on the conventional Reynolds averaged moments. This method is more economical in the sense that it halves the number of partial differential equations to be solved. The proposed K–ε–γ model has been applied to compute a plane jet, a round jet, a plane far wake and a plane mixing layer. The computational results of the model show considerable improvement over previous models for all these shear flows. In particular, the spreading rate, the centreline mean velocity and the profiles of Reynolds stresses and turbulent kinetic energy are calculated with significantly improved accuracy.

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