Numerical Modeling of Heat Transfer in Taylor-Couette-Poiseuille Systems
Bibliographic record
Abstract
The purpose of this work is to model turbulent Taylor-Couette-Poiseuille flows submitted to a temperature gradient. These flows are relevant in many industrial applications including rotating machineries and more especially for the effective cooling of electric motors. Several turbulence closures (k-ω SST, RSM and LES) are first compared in the isothermal case and validated against the reliable experimental data of Escudier and Gouldson [1]. A detailed analysis of the coherent structures within the boundary layers is proposed. The model offering the best compromise between computational cost and accuracy is then used to perform more computations in the configuration with a temperature gradient considered by Kuosa et al. [2]. In their system, the air flow enters the rotor-stator cavity radially. Correlations for the average Nusselt numbers along the rotor and stator as a function of the control parameters (rotation rate, air flow rate, Prandtl number) are provided and compared with data available in the literature [3].
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".