New IAEA Coordinated Research Project on Thermal-Hydraulics of Supercritical Water Cooled Reactors
Bibliographic record
Abstract
In view of the high interest among a number of Member States in the Supercritical Water Cooled Reactor (SCWR) concept, the IAEA launched the second Coordinated Research Project (CRP) on thermal-hydraulics of SCWRs, entitled “Understanding and Prediction of Thermal-Hydraulics Phenomena Relevant to SCWRs” in 2014 to foster international collaboration. The key objectives of this new CRP are to (i) improve the understanding and prediction accuracy of thermal-hydraulics phenomena relevant to SCWRs and (ii) benchmark numerical toolsets for their analyses. At present, 12 institutes participate in the CRP from 10 IAEA Member States, and the OECD/NEA is in cooperation, based on a special agreement with the IAEA, to host a database housing experimental and analytical results contributed from the CRP participants. The expected outcomes from this CRP include (i) enhancement of the understanding of thermal-hydraulics phenomena, (ii) sharing of experimental and analytical results, and the prediction methods for key thermal-hydraulics parameters, and (iii) cross-training of personnel between participating institutes through their close interactions and collaboration. This paper describes the plan of the new CRP: overall and specific research objectives; tasks and sub-tasks; schedule; and expected outcomes and outputs. It also introduces briefly other IAEA activities to facilitate and support R&D for SCWR technology in Member States, which include technical meetings and training courses.
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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 | 0.023 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".