Optimization of small modular nuclear reactor integration at a remote mine site in Canada
Bibliographic record
Abstract
The concept of design envelope energy system optimization was developed and used to investigate \nthe feasibility of small modular reactor (SMR) deployment at a remote off-grid mine in northern \nCanada. A set of design envelope demands was produced based on engineering estimates to \nrepresent the anticipated actual nominal and peak demands of the mine, with a focus on \npreserving characteristic variability on a per-utility basis. The formulation of design envelope \noptimization was successful in optimizing a mine’s energy supply system given a design envelope of \nnominal and peak energy demands to ensure the peak demand could always be satisfied, as \ndemonstrated through optimization of a wind-diesel hybrid system. A SMR was integrated into \nthe optimal mine site energy supply (OMSES) optimization model. However, the SMR was not an \neconomic solution for the mine given the economic circumstances of the project. The high specific \ncapital cost of the SMR was not competitive against an incumbent wind-diesel hybrid system. \nTherefore, additional opportunities to integrate a SMR more deeply into a mine’s operation were \nconceptualized and proposed for future work.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".