Core Design Optimization and Steady State Criticality Analysis of the Canadian Nuclear Battery™
Bibliographic record
Abstract
The nuclear microreactor, although not a novel concept, is a fast-emerging technology. Microreactors are small modular reactors that have a thermal power level between 1 and 20 MW. They take the smallness and modularity to a whole new level in the sense that they are entirely factory-built and shipped to the intended location, rather than constructed onsite. One such design is the 2400 kWth Canadian Nuclear Battery™ (CNB) design being developed by Dunedin Energy System Ltd. for use in remote northern territories as a potential alternative to diesel electric power plants. Key technical features of the reactor include a heat pipe cooled core, graphite neutron moderator, high assay low enriched uranium (HALEU), TRISO coated fuel particle and use of burnable poison particles for long term reactivity control. This thesis reports the methodology used for 3D neutronics modeling and core design of the CNB using the Monte Carlo particle transport code SERPENT 2.1. Optimization of the fuel enrichment, amount of burnable poison, lattice pitch, and poison particle size is carried out by performing burnup calculations to achieve a reasonable reactivity swing over 20 years of full power operation without refueling. The worth of the reactivity control system, shutdown margin, fuel and graphite temperature reactivity coefficients, coolant void coefficients, neutron flux , and power distribution over the reactor lifetime are evaluated. Additionally, a preliminary single lattice cell thermal-hydraulic and neutronic coupling is performed along with a viability study of the control drum system as an alternative form of reactivity control.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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) | 0.004 | 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".