Assessment of Computational Tools in Support of Heat-Transfer Correlation Development for Fuel Assembly of Canadian Supercritical Water-Cooled Reactor
Bibliographic record
Abstract
Experimental data and correlations are not available for the fuel-assembly concept of the Canadian supercritical water-cooled reactor (SCWR). To facilitate the safety analyses, a strategy for developing a heat-transfer correlation has been established for the fuel-assembly concept at supercritical pressure conditions. It is based on an analytical approach using a computational fluid dynamics (CFD) tool and the ASSERT subchannel code to establish the heat transfer in supercritical pressure flow. Prior to the application, the CFD tool was assessed against experimental heat transfer data at the pseudocritical region obtained with bundle subassemblies to identify the appropriate turbulence model for use. Beyond the pseudocritical region, where the normal heat transfer behavior is anticipated, the ASSERT subchannel code also was assessed with appropriate closure relationships. Detailed information on the supporting experiments and the assessment results of the computational tools are presented.
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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 | 0.002 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".