Bibliographic record
Abstract
The underground storage of used nuclear fuel in Deep Geologic Repositories (DGRs) has been a subject of research in Canada for decades. One important technical aspect of repository design is the accommodation of the mechanical impacts of thermal inputs (heating) from the fuel as it goes through the remainder of its life cycle. Placement room spacing, a major factor in project cost, will be determined by the ability of the host rock to dissipate heat. The thermal conductivity and linear thermal expansion will determine the evolution of the temperature and thermally-induced stress fields. Thermal processes must be well understood to design a successful DGR. \n \nThis thesis examines the thermal properties of rocks, how they are influenced by factors such as temperature, pressure, mineralogy, porosity, and saturation; and common methods for calculating and/or measuring these properties. A brief overview of thermal and thermally-coupled processes in the context of DGRs demonstrates the degree to which they would impact design, construction, and operation of these critical structures. Several case histories of major in situ heating experiments are reviewed to determine how the lessons learned could be applied to a Canadian Underground Demonstration Facility (UDF). \n \nA mineralogy investigation using X-Ray Diffraction (XRD) and Scanning Electron Microscopy (SEM) examines samples of the Cobourg Limestone from the Bowmanville and Bruce sites, and demonstrates geographical variability within the Cobourg Formation. The thermal properties of samples from the Bowmanville site are determined. A divided bar apparatus was constructed and used to measure thermal conductivity. The temperature measurement component of the divided bar apparatus was used to measure linear thermal expansion. Finally, the past investigations into the thermal impact of a DGR are reviewed, and the implications of the laboratory testing results on similar analyses are discussed.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".