Temperature feedback reactivity analysis for LEU-Fuelled SLOWPOKE-2 research reactor using DRAGON5 and DONJON5 codes
Bibliographic record
Abstract
The purpose of this study is to provide a new deterministic model for the SLOWPOKE-2 nuclear research reactor at École Polytechnique de Montréal (EPM) with LEU (Low Enriched Uranium) core. Using the latest release of the code system DRAGON5 and DONJON5 and the cross-section data library ENDFB.VII rel.1 evaluation, the developed model is applied to simulate the neutronic behavior of the SLOWPOKE-2 research reactor. We studied the separate temperature effects of the main components of the core (i.e., fuel, coolant/moderator, beryllium reflector, and water reflector). The contribution of different physical phenomena to the RTC was assessed. The temperature reactivity feedback calculated using the deterministic approach based on the DRAGON5 and DONJON5 code system using the ENDF/B-VII.1 evaluated nuclear data library produced in the WIMD-D4 format is in good agreement. Therefore, this work proves the capability of DRAGON5 and DONJON5 codes, normally used for power reactors, to reliably simulate a low-power research reactor.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".