The thermal behavior and ice saturation of a developed zero-cement backfill used in a novel technique in Arctic mining
Bibliographic record
Abstract
• Investigation of thermal behavior of zero-cement backfill in which frozen water used as binder over two years. • Highlighting the role of ice saturation as a critical factor in the thermomechanical performance of backfill materials. • Analysis of the sensitivity of cooling rates to geometric properties and other influential factors. • Observation that deeper backfill points freeze more slowly due to higher pressure, despite faster cooling rates. Mining in Arctic and permafrost regions presents unique operational challenges, particularly due to extreme climatic conditions and logistical difficulties. This study focuses on zero-cement backfill as a novel approach in cold-region mining, where frozen water, instead of cement, provides structural integrity. The research investigates the thermal behavior of this backfill material, with an emphasis on two key factors: temperature evolution and ice saturation, using the Chidliak diamond mine in Nunavut, Canada, as a case study. Numerical simulations over a 720-day period were conducted to model the backfilling process in adjacent mine shafts, with the results revealing how thermal dynamics unfold at various depths and positions. The findings show that deeper points in the backfill experience faster cooling rates due to their proximity to colder surrounding rock, while ice saturation, a critical indicator of backfill stability, evolves more slowly at greater depths due to the pressure inhibiting ice formation. Acknowledging the significance of temperature evolution, ice saturation plays a crucial role in the thermomechanical analysis of backfill due to its profound impact on the mechanical behavior and solidification of the material. The time interval between when the temperature at each cut point drops below −0.1 °C and when the ice saturation at that point reaches 0.1 varies from approximately 1 to 61 days, underscoring the importance of ice saturation. Additionally, the study highlights the significance of cooling rates and freezing times, showing that variations in horizontal and vertical shaft positions affect temperature distribution and ice formation, ultimately impacting operational planning and mine stability. This research contributes to the growing understanding of frozen backfill techniques in permafrost regions. The results provide insights for optimizing backfilling strategies, improving cost-efficiency, and ensuring safety in Arctic mining operations. By addressing the complexities of frozen backfill in terms of thermal and mechanical properties, this study aids in advancing sustainable mining practices in cold, remote regions.
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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".