Molten Fuel Moderator Interaction Program at Chalk River Laboratories
Bibliographic record
Abstract
The Canadian nuclear power generation industry, represented by the CANDU Owners Group (COG), has been funding an experimental program at Chalk River Laboratories (CRL) to study the interaction between molten material ejected from a fuel channel and the moderator. These experiments were designed to address one of the very low probability postulated accident events considered for CANDU 1 Pressurized Heavy Water Reactors. The reactor consists of an array of horizontal fuel channels that contain the UO2 nuclear fuel and high-temperature, high-pressure heavy water coolant. Under severely restricted flow blockage conditions, approaching 100% reduction of the flow area, postulated in a fuel channel, the temperature excursion could result in fuel melting, consequential failure of the fuel channel, and ejection of the molten fuel at high pressures into the heavy water moderator at near atmospheric pressure. In preparation for these tests, a chemical mixture called a thermite, that could produce a simulated molten fuel when ignited, was developed in partnership with Argonne National Laboratory (USA). Following this thermite development, two base-case reference tests were completed. The two base-case reference tests, with no molten material present, were performed in the Molten-Fuel Moderator-Interaction (MFMI) facility at CRL. Following the base-case reference tests, a high-pressure melt ejection test using prototypical corium was conducted. The objectives of this paper are to provide an overview of the MFMI program and present the results obtained from thermite development, base-case and melt ejection experiments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 0.003 |
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".