CORE DESIGN OF BREED & BURN MOLTEN SALT FAST REACTOR
Bibliographic record
Abstract
Previous designs of once-through solid-fuelled breed-and-burn (B&B) reactor and the conventional molten salt reactor (MSR) concepts suffer from material limitation of neutron irradiation damage and chemical corrosion. A novel breed-and-burn molten salt reactor (BBMSR) concept uses separate molten salt fuel and coolant in a linear assembly core configuration. Similar to Moltex Energy Stable Salt Reactor (SSR) design, the configuration with fuel salt contained in fuel tubes and coolant salt in pool type reactor vessel has been previously studied. The study confirmed that breed-and-burn operation is feasible in principle, however with a low neutronic margin. The objective of this paper was to seek improvements of the neutronic margin with a metallic natural uranium blanket design. A parametric study was performed for the natural uranium blanket design. BBMSR neutronic performance simulation was modelled using Serpent, a Monte Carlo reactor physics code, with a single 3D hexagonal channel containing a single fuel tube in an infinite lattice with reflective radial and vacuum axial boundary conditions. The addition of a metallic natural uranium blanket inside the fuel tube, which increases the natural uranium metal to fuel salt ratio (ϒ) of the BBMSR, was shown to significantly increase the neutronic performance of the BBMSR.
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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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".