Modeling Subcooled Flow Film Boiling in a Vertical Tube
Bibliographic record
Abstract
A two-fluid one-dimensional model has been developed to predict the wall temperature of an internally heated tube during inverted annular flow film boiling (IAFB). The model is derived using basic conservation equations of mass, momentum, and energy. To simplify the derivation of the constitutive heat transfer relations, flow between two parallel plates is assumed. The model features shear stress and interfacial relations that make it accurately predict the parametric effects and heat transfer characteristics of IAFB over a wide range of flow conditions. The model predicts wall temperatures of R-134a-cooled tubes with an average error of −1.21% and a rms error of 6.37%. This corresponds to average and rms errors in predicted heat transfer coefficients of 1.33% and 10.07%, respectively. Using water data, the model predicts wall temperatures with an average error of −1.76% and a rms error of 7.78%, which corresponds to average and rms errors in predicted heat transfer coefficients of 4.16% and 15.06%, respectively.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".