Optimization of the Spatial Mesh for Numerical Solution of the Neutron Transport Equation in a Cluster-Type Lattice Cell
Bibliographic record
Abstract
For programs that solve the neutron transport equation with an approximation that the neutron flux is constant in each space in a user-defined mesh, optimization of that mesh yields benefits in computing time and attainable precision. The previous best practice does not optimize the mesh thoroughly, because a large number of test runs of the solving software would be necessary. The method presented here optimizes the mesh for a flux that is based on conventional approximations but is more informative, so that a minimal number of parameters, one per type of material, must be adjusted by test runs to achieve thorough optimization. For a 37 element, natural-uranium, CANDU ® lattice cell, the present optimization yields 7 to 12 times (depending on the criterion) better precision than the previous best practice in 37% less computing time.
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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".