Thermal-hydraulic Phenomena List
Bibliographic record
Abstract
A list of 116 Thermal-Hydraulic Phenomena T-HP is derived in the present paper following documents issued during the last three decades by the Committee on the Safety of Nuclear Installations of Nuclear Energy Agency of The Organization for Economic Cooperation and Development (OECD/NEA/CSNI) and by the International Atomic Energy Agency (IAEA). The list includes consideration of experiments performed in Separate Effect Test (SET) and Integral Effect Test (IET) facilities relevant to Reactor Coolant System and Containment of Water Cooled Nuclear Reactors (WCNR). A dozen WCNR types are considered: Pressurized Water Reactors (PWR), Boiling Water Reactors (BWR), Russian designs (VVER-440, VVER-1000 and RBMK), pressure tube heavy water reactor designs by Canada (CANDU) and India (PHWR) and so-called ‘advanced’ reactors (e.g. AP-1000 and APR-1400 designed in US and Korea, respectively). \nA variety of applications for the T-HP list is envisaged in nuclear thermal-hydraulics, e.g. a) to address the scaling issue; b) perform uncertainty evaluations; c) to characterize constitutive equations and ‘special models’ for modeling purposes; d) to prioritize research in nuclear reactor thermal-hydraulics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".