Thermal-Hydrological-Chemical Modeling of a Covered Waste Rock Pile in a Permafrost Region
Bibliographic record
Abstract
In order to reduce contaminant mass loadings, thermal cover systems may be incorporated in the design of waste rock piles located in regions of continuous permafrost. In this study, reactive transport modeling was used to improve the understanding of coupled thermo-hydrological and chemical processes controlling the evolution of a covered waste rock pile located in Northern Canada. Material properties from previous field and laboratory tests were incorporated into the model to constrain the simulations. Good agreement between simulated and observational temperature data indicates that the model is capable of capturing the coupled thermo-hydrological processes occurring within the pile. Simulations were also useful for forecasting the pile’s long-term evolution with an emphasis on water flow and heat transport mechanisms, but also including geochemical weathering processes and sulfate mass loadings as an indicator for the release of contaminated drainage. An uncertainty analysis was carried out to address different scenarios of the cover’s performance as a function of the applied infiltration rate, accounting for the impacts of evaporation, runoff, and snow ablation. The model results indicate that the cover performance is insensitive to the magnitude of recharge rates, except for limited changes of the flow regime in the shallow active layer. The model was expanded by performing an additional sensitivity analysis to assess the role of cover thicknesses. The simulated results reveal that a cover design with an appropriate thickness can effectively minimize mass loadings in drainage by maintaining the active layer completely within the cover.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".