PHWR Reactivity Device Incremental Macroscopic Cross Sections and Reactivities for a Molybdenum-Producing Bundle and a Standard Bundle
Bibliographic record
Abstract
A new 37-element PHWR fuel bundle, designed for molybdenum-99 production, has been proposed previously. The new bundle has been shown to have lattice properties and reactivity feedback effects equivalent to the standard PHWR bundle. This study looks at the effect the use of molybdenum-99-producing bundles has on the reactivity worth of reactivity devices, through the prism of reactivity-device macroscopic-cross-section increments. The study utilizes three-dimensional supercell configurations and the neutron transport code DRAGON to calculate and compare the incremental macroscopic cross sections and supercell reactivity for adjuster absorbers, shutoff absorber rods and liquid zone controllers when surrounded by molybdenum-99-producing bundles and by regular bundles. Two geometrical representations of fuel bundles are used: a detailed, cluster, representation, whereby all fuel pins are modeled separately, and an annularized representation, whereby each ring of fuel pins and corresponding coolant is represented as a homogeneous annulus. The latter model is the one customarily used in production calculations for finding cross-section increments of reactivity devices.The study finds that reactivity-device cross-section and supercell reactivity increments are very similar (< 2% difference in reactivity increments) for the case of the molybdenum-producing bundle and the regular bundle. The study also finds that the use of a detailed, cluster, geometrical representation of the fuel bundle produces slightly different cross-section increments and supercell reactivity increments than the use of an annularized geometrical representation. The supercell reactivity-increment difference between the two representations is found to be ~8.0% for adjuster absorbers and ~11.0% for shutoff absorber rods.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".