2006
DOI: 10.2514/1.22650
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Evaluation of Modified Two-Equation Turbulence Models for Jet Flow Predictions

Abstract: Three two-equation turbulence models developed specifically to improve prediction of jet flowfields are investigated. These models are the Tam-Ganesan k-" formulation, a standard k-" model with modification for heated jets referred to as the PAB temperature correction, and a standard k-" model employing variable diffusion for the k and " equations. Two standard two-equation models are also investigated for comparison with the modified formulations. The standard models are the Chien k-" and Menter shear stress … Show more

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Cited by 66 publications
(34 citation statements)
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References 29 publications
(73 reference statements)
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“…However, there are differences between the k-ε models that can justify the different performance found in this study. As mentioned in [38] the differences between this model and the exact transformation of the ε-equation of the standard k-ε to an u-equation results in an extra diffusion term that is not included in the SST model. Also, as reported in [39], the u-equation diffusion coefficient has a value of s u2 ¼ 1=s ε ¼ 1=1:3 ¼ 0:769, whereas in SST s u2 0:857 which corresponds to s ε ¼ 1:17.…”
Section: Discussionmentioning
confidence: 96%
“…However, there are differences between the k-ε models that can justify the different performance found in this study. As mentioned in [38] the differences between this model and the exact transformation of the ε-equation of the standard k-ε to an u-equation results in an extra diffusion term that is not included in the SST model. Also, as reported in [39], the u-equation diffusion coefficient has a value of s u2 ¼ 1=s ε ¼ 1=1:3 ¼ 0:769, whereas in SST s u2 0:857 which corresponds to s ε ¼ 1:17.…”
Section: Discussionmentioning
confidence: 96%
“…Numerical analysis of the fluid flow was based on the continuity and momentum equations [25,35], which are expressed as Equations (3) and (4) as follows, respectively:…”
Section: Governing Equationsmentioning
confidence: 99%
“…Despite these improvements, RANS still lacks robustness and consistency in their jet flow predictions. Factors like jet flow mixing, growth of instabilities or potential core length simulation are challenging in RANS [33], and standard calibrations from other CFD problems do not work often, being necessary to find an appropriate turbulent model parameter setting [22]. All these drawbacks in the prediction, summed to the already mentioned drawbacks inherent to using fixed values for physical conditions, lead to the necessity of providing extra metrics of reliability in the simulations.…”
Section: Introductionmentioning
confidence: 99%