Comparison between EVM and RSM turbulence models in predicting flow and heat transfer in rib-roughened channels
Bibliographic record
Abstract
A 3D analysis of two-equation eddy viscosity (EVMs) and Reynolds stress (RSM) turbulence models and their application to solve flow and heat transfer in rotating rib-roughened internal cooling channels is the main focus of this study. The flow in these channels is affected by ribs, rotation, buoyancy, bends and boundary conditions. The EVMs considered are the standard k–ϵ model of Launder and Spalding [1 Launder, B. E. and Spalding, D. B. 1972. Lectures in Mathematical Models of Turbulence, London, , England: Academic. [Google Scholar]], the renormalization group k–ϵ model of Yakhot and Orszag [2 Yakhot, V. and Orszag, S. A. 1986. Renormalization group analysis of turbulence: I. Basic theory. Journal of Scientific Computing, 1: 1–51. [CSA] [Google Scholar]], the realizable k–ϵ model of Shih et al. [3 Shih, T.-S., Liou, W. W., Shabbir, A., Yang, Z. and Zhu, J. 1995. A new k-e eddy viscosity model for high Reynolds number turbulent flows. Computers and Fluids, 24: 227–238. [CSA] [Google Scholar]], the standard k–ω model of Wilcox [4 Wilcox, D. C. 1998. Turbulence Modeling for CFD, 2nd, La Canada, California: DCW Industries, Inc.. [Google Scholar]] and the shear–stress transport (SST) k–ω model of Menter [5 Menter, F. R. 1994. Two-equation eddy-viscosity turbulence models for engineering applications. AIAA Journal, 32: 1598–1605. [CSA] [Google Scholar]]. The viscosity-affected near-wall region is resolved by enhanced near-wall treatment using combined two-layer model with enhanced wall functions. The results for both stationary and rotating channels showed the advantages of Reynolds stress model (RSM), Gibson and Launder [6 Gibson, M. M. and Launder, B. E. 1978. Ground effects on pressure fluctuations in the atmospheric boundary layer. Journal of Fluid Mechanics, 86: 491–511. [CSA] [Google Scholar]], Launder [7 Launder, B. E. 1989. Second-moment closure: present … and future?. International Journal of Heat and Fluid Flow, 10: 282–300. [CSA] [Google Scholar]] and Launder et al. [8 Launder, B. E., Reece, G. J. and Rodi, W. 1975. Progress in the development of a Reynolds-stress turbulence closure. Journal of Fluid Mechanics, 68: 537–566. [CSA] [Google Scholar]] in predicting the flow field and heat transfer compared to two-equation EVMs that need corrections to account for streamline curvature, buoyancy and rotation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".