scholarly journals Numerical and Experimental Examination of Turbulent Mixing of Heated Jet in Crossflow

2020 ◽  
Vol 34 (2) ◽  
pp. 230-242
Author(s):  
Michael R. Borghi ◽  
Douglas Thurman ◽  
Philip Poinsatte ◽  
William Engblom
Keyword(s):  
Turbulent Mixing ◽  
Experimental Examination ◽  
Jet In Crossflow ◽  
Heated Jet

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 modeling of turbulent mixing in a jet in crossflow

2013 ◽  
Vol 41 ◽  
pp. 55-65 ◽  
Author(s):  
Flavio Cesar Cunha Galeazzo ◽  
Georg Donnert ◽  
Camilo Cárdenas ◽  
Julia Sedlmaier ◽  
Peter Habisreuther ◽  
...  
Keyword(s):  
Computational Modeling ◽  
Turbulent Mixing ◽  
Jet In Crossflow

Turbulent mixing in non-isothermal jet in crossflow

2015 ◽  
Vol 89 ◽  
pp. 1239-1257 ◽  
Author(s):  
Mostafa Esmaeili ◽  
Asghar Afshari ◽  
Farhad A. Jaberi
Keyword(s):  
Turbulent Mixing ◽  
Jet In Crossflow

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.

Turbulent mixing in uniform channels of irregular cross-section

1994 ◽  
Vol 32 (1) ◽  
pp. 67-86 ◽  
Author(s):  
R. I. Nokes ◽  
G. O. Hughes
Keyword(s):  
Cross Section ◽  
Turbulent Mixing
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