scholarly journals Robust Bayesian Calibration of a RANS Model for Jet-in-Crossflow Simulations

2017 ◽  
Author(s):  
Jaideep Ray ◽  
Sophia Lefantzi ◽  
Srinivasan Arunajatesan ◽  
Lawrence J. DeChant
Keyword(s):  
Bayesian Calibration ◽  
Rans Model ◽  
Jet In Crossflow

scholarly journals Robust Bayesian Calibration of a k−ε Model for Compressible Jet-in-Crossflow Simulations

AIAA Journal ◽  
2018 ◽  
Vol 56 (12) ◽  
pp. 4893-4909 ◽  
Author(s):  
Jaideep Ray ◽  
Lawrence Dechant ◽  
Sophia Lefantzi ◽  
Julia Ling ◽  
Srinivasan Arunajatesan
Keyword(s):  
Bayesian Calibration ◽  
Jet In Crossflow ◽  
Compressible Jet

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

2012 ◽  
Author(s):  
Elizaveta Ivanova ◽  
Berthold Noll ◽  
Manfred Aigner
Keyword(s):  
Schmidt Number ◽  
Numerical Study ◽  
Scalar Fields ◽  
Navier Stokes ◽  
Rans Model ◽  
Eddy Simulation ◽  
Eddy Viscosity Model ◽  
Jet In Crossflow ◽  
Turbulent Schmidt Number ◽  
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 WALE (Wall-Adapted Local Eddy Viscosity) 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.

Numerical Simulation of an Axial Reacting Jet-in-Crossflow at Elevated Pressure

2021 ◽  
Author(s):  
Bernhard Stiehl ◽  
Michelle Otero ◽  
Tommy Genova ◽  
Kareem A. Ahmed ◽  
Scott M. Martin
Keyword(s):  
Numerical Simulation ◽  
Elevated Pressure ◽  
Jet In Crossflow

RANS Model development on temperature variance in conjugate heat transfer

2020 ◽  
pp. 1-28
Author(s):  
Gaoqiang Yang ◽  
Hector Iacovides ◽  
Timothy Craft ◽  
David Apsley
Keyword(s):  
Heat Transfer ◽  
Conjugate Heat Transfer ◽  
Model Development ◽  
Temperature Variance ◽  
Rans Model
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