Studies of the Thermalhydraulics Subchannel Code ASSERT-PV 3.2-SC for Supercritical Applications
Bibliographic record
Abstract
Abstract Over the last decade, several international thermalhydraulics benchmarking efforts have been carried out to support the development of the Generation IV supercritical water-cooled reactor (SCWR) concept. These benchmarking efforts aimed to assess the readiness of computer codes to predict the thermalhydraulics behavior of supercritical fluids for nuclear fuel assembly applications. The results from the benchmarking also shed light on knowledge gaps. Throughout the years, several advancements in this area have been achieved, resulting in relevant conclusions and observations. Furthermore, experimental campaigns have been carried out worldwide to further our knowledge on the thermalhydraulics of supercritical fluids. The nuclear industry uses the subchannel approach to study the thermalhydraulics behavior of nuclear fuel assemblies in detail. In Canada, the subchannel code advanced solution of subchannel equations in reactor thermalhydraulics—pressure velocity (ASSERT-PV) is the qualified code for subchannel applications. ASSERT-PV was modified to handle supercritical conditions, resulting in an interim code version. This publication presents relevant subchannel analyses using the interim supercritical version of ASSERT-PV for fuel assemblies cooled with supercritical fluids.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".