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.

Unsteady Simulations of Flow Field and Scalar Mixing in Transverse Jets

2009 ◽  
Author(s):  
Elizaveta Ivanova ◽  
Massimiliano Di Domenico ◽  
Berthold Noll ◽  
Manfred Aigner
Keyword(s):  
Large Scale ◽  
Quantitative Prediction ◽  
Navier Stokes ◽  
Scalar Mixing ◽  
Combustion Chambers ◽  
Mixing Processes ◽  
Transverse Jets ◽  
Vortical Structures ◽  
Jet In Crossflow ◽  
Reynolds Averaged Navier Stokes

This paper presents numerical simulations of flow and scalar mixing in two different jet in crossflow configurations. The testcases are chosen to resemble the dilution mixing processes in gas turbine combustion chambers. Unsteady simulations employing two different computational approaches are presented: unsteady Reynolds-Averaged Navier-Stokes (URANS) and Scale-Adaptive Simulations (SAS). The results obtained by each method are compared, analyzed, and validated against experimental data. The importance of the reproduction of the large-scale unsteady coherent vortical structures in the numerical simulation is demonstrated. Both URANS and SAS revealed the typical jet in crossflow vortical structures. The SAS method was able to resolve smaller structures than URANS on the same computational grid. The quantitative prediction accuracy of time-averaged velocities and temperatures is satisfactory for both methods. In contrast, the steady-state Reynolds-Averaged Navier-Stokes (RANS) computations failed for the present testcases.

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.

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.

scholarly journals Lagrangian views on turbulent mixing of passive scalars

2010 ◽  
Vol 368 (1916) ◽  
pp. 1561-1577 ◽  
Author(s):  
Katepalli R. Sreenivasan ◽  
Jörg Schumacher
Keyword(s):  
Data Analysis ◽  
Turbulent Mixing ◽  
Passive Scalar ◽  
Navier Stokes ◽  
Scalar Mixing ◽  
Passive Scalars ◽  
Scalar Turbulence ◽  
Kraichnan Model ◽  
Lagrangian Turbulence

The Lagrangian view of passive scalar turbulence has recently produced interesting results and interpretations. Innovations in theory, experiments, simulations and data analysis of Lagrangian turbulence are reviewed here in brief. Part of the review is closely related to the so-called Kraichnan model for the advection of the passive scalar in synthetic turbulence. Possible implications for a better understanding of the passive scalar mixing in Navier–Stokes turbulence are also discussed.

scholarly journals Passive Scalar Mixing Downstream of a Synthetic Jet in Crossflow

2008 ◽  
pp. 103-109
Author(s):  
Glen Mitchell ◽  
Emmanuel Benard ◽  
Václav Uruba ◽  
Richard Cooper
Keyword(s):  
Passive Scalar ◽  
Synthetic Jet ◽  
Scalar Mixing ◽  
Jet In Crossflow

A strategy for large-scale scalar advection in large eddy simulations that use the linear eddy sub-grid mixing model

2018 ◽  
Vol 28 (10) ◽  
pp. 2463-2479 ◽  
Author(s):  
Salman Arshad ◽  
Bo Kong ◽  
Alan Kerstein ◽  
Michael Oevermann
Keyword(s):  
Turbulent Mixing ◽  
Large Scale ◽  
Molecular Diffusion ◽  
Passive Scalar ◽  
Mixing Model ◽  
Large Eddy Simulations ◽  
High Flux ◽  
Scalar Mixing ◽  
Content Type ◽  
Large Eddy

PurposeThe purpose of this numerical work is to present and test a new approach for large-scale scalar advection (splicing) in large eddy simulations (LES) that use the linear eddy sub-grid mixing model (LEM) called the LES-LEM.Design/methodology/approachThe new splicing strategy is based on an ordered flux of spliced LEM segments. The principle is that low-flux segments have less momentum than high-flux segments and, therefore, are displaced less than high-flux segments. This strategy affects the order of both inflowing and outflowing LEM segments of an LES cell. The new splicing approach is implemented in a pressure-based fluid solver and tested by simulation of passive scalar transport in a co-flowing turbulent rectangular jet, instead of combustion simulation, to perform an isolated investigation of splicing. Comparison of the new splicing with a previous splicing approach is also done.FindingsThe simulation results show that the velocity statistics and passive scalar mixing are correctly predicted using the new splicing approach for the LES-LEM. It is argued that modeling of large-scale advection in the LES-LEM via splicing is reasonable, and the new splicing approach potentially captures the physics better than the old approach. The standard LES sub-grid mixing models do not represent turbulent mixing in a proper way because they do not adequately represent molecular diffusion processes and counter gradient effects. Scalar mixing in turbulent flow consists of two different processes, i.e. turbulent mixing that increases the interface between unmixed species and molecular diffusion. It is crucial to model these two processes individually at their respective time scales. The LEM explicitly includes both of these processes and has been used successfully as a sub-grid scalar mixing model (McMurtry et al., 1992; Sone and Menon, 2003). Here, the turbulent mixing capabilities of the LES-LEM with a modified splicing treatment are examined.Originality/valueThe splicing strategy proposed for the LES-LEM is original and has not been investigated before. Also, it is the first LES-LEM implementation using unstructured grids.

Increasing the Passive Scalar Mixing Quality of Jets in Crossflow With Fluidics Actuators

2011 ◽  
Vol 134 (2) ◽  
Author(s):  
Arnaud Lacarelle ◽  
Christian O. Paschereit
Keyword(s):  
High Speed ◽  
Passive Scalar ◽  
Mixing Efficiency ◽  
Scalar Mixing ◽  
Jet In Crossflow ◽  
Mixing Quality ◽  
Single Jet ◽  
Pulsating Jets ◽  
The One

Jets in crossflow are widely used in the industry for homogenization or cooling tasks. Recently, pulsating jets have been investigated as a mean to increase the scalar mixing efficiency of such configurations, whether for a single jet or for an array of jets. To avoid the disadvantages of mechanically actuated flows (costs, maintenance), a new injector based on a fluidics oscillator has been designed. Four injectors have been implemented in a generical jet in crossflow configuration and the mixing efficiency of the setup was compared with the one of the same setup equiped with standard non oscillating jets. With help of high-speed concentration measurement technique, the scalar mixing quality of both setups was measured at three positions downstream of the injection plane. In all the cases tested, the fluidics injectors present a better temporal homogenization, characterized by the Danckwerts unmixedness criterion, than the standard jets. For a defined mixing quality, a decrease of the mixing length by approximately 50% can be achieved with the fluidics injectors. Furthermore, the new injectors exhibit a mixing quality which is less sensitive to variations of the jet to crossflow momentum. The flapping motion of the fluidics injectors induces a wider azimuthal spreading of the fluidics jets immediately downstream of the injection location. This increases the macro- and micro-mixing phenomea which lead then to the high gains in mixing quality. It is thus demonstrated that fluidics oscillators present a strong potential to improve the passive scalar homogenization of jet in crossflow configurations.

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.

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