Assessment of Look-up tables for the prediction of heat transfer coefficient distribution in rod bundles cooled by supercritical water
Bibliographic record
Abstract
The evaluation of available Look-Up Tables for prediction of heat transfer coefficient distribution in rod bundles cooled by supercritical water with the aim of their further use in computational analyses of various Fuel Assembles of Supercritical Water-Cooled Reactors is made. The comparison between the calculations based on Look-Up Tables with the values from empirical correlations and experimental data for smooth and wire-wrapped rod bundles was presented. The obtained results showed that Look-Up Table of the University of Ottawa, which was created to describe improved and deteriorated heat transfer regimes in round tubes, allows describing available data points with 30 % of the mean square deviation. It is noted that the presence of wire intensifies heat transfer exchange near pseudocritical temperature region but existing versions of Look-Up Tables cannot take into account this effect. Nevertheless, there is potential for further improvement in predicting the heat transfer coefficient using Look-Up Table by introducing additional correction factors.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".