Reconstruction of Intra-Bundle Fission Density Profile during a Postulated LOCA in a CANDU Reactor
Bibliographic record
Abstract
In this paper, results related to the reconstruction of intra-bundle fission density profile for a 37-pin CANDU-6 bundle with the highest enthalpy deposition during a postulated large LOCA stagnation break in a Bruce B core are presented. Bruce B is a nuclear power plant in Kincardine, Ontario (Canada)), on the shores of Lake Huron with 4 CANDU reactors that are rated at about 750 MWe. The reconstruction of the fuel pin fission densities is based on steady-state, three-dimensional simulations with the Monte Carlo code MCNP for a subset of 27 out of 69 time steps during the first two seconds of the power pulse predicted for the fuel bundle at core location V13/8. Two-group cross section data libraries are generated for MCNP at each time step by the lattice depletion neutron transport code HELIOS-1.7. To include the effect of the surrounding core environment, the calculations are performed with time-dependent albedo boundary conditions inferred from a full core simulation of the transient by the nodal diffusion code NESTLE with HELIOS homogenized cross-sections. It is found that the local peaking factor (LPF) in the outer ring varies during the transient, but never exceeds its value before the transient. Inclusion of the coremore » environment increases the LPF in the outer ring. For the analyzed case, the increase is 0.72% with a relative error of 0.01% for the LPF before the transient and 0.55% (with a relative error of 0.01%) for the maximum average LPF during the transient. The latter is based on only four selected transient time points. Note that the immediate environment of the 'hot bundle' does not contain any reactivity devices or other perturbing factors. As a result, the increases observed in the LPF in the outer ring may not be representative of the situations in which 'other' core environment perturbing factors are present. To determine the effect of these factors on the LPF, further analyses of a bundle in the proximity of control devices should be carried out. (authors)« less
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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 | 0.000 | 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) | 0.000 | 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".