Numerical Modeling of Gas Flow in the Suncor Coke Stockpile Covers
Bibliographic record
Abstract
The occurrence of thermally driven convective air flow within waste rock or natural soil profiles has been well established; however, the potential impact that convective air flow may have on water storage within reclamation soil covers has not been previously explored. We conducted a numerical modeling study to evaluate the effect that convective air flow may have on stored water within a soil reclamation cover placed over a coke stockpile at an oil sands mine in Alberta, Canada. Coke is a carbon, sand‐like byproduct of heavy oil processing. Two‐dimensional simulations of thermally driven convective air flow were conducted for two different field sites based on available field data. The elevated temperature within the coke stockpile resulted in the development of strong convective air flow cells that drew in drier atmospheric air over the lower slope positions while releasing it across the upper slope and plateau areas of the cover. The magnitude of the gas flux and the intensity of the convection within the cell were a function of the air permeability of the coke and cover material, the depth of the coke, and the slope of the stockpile. It was estimated that convective air movement through the cover could produce as much as 1 to 2 mm/d of enhanced drying of the cover in lower slope positions. Field observations of water content distributions within the cover provided corroboration that the cover has undergone enhanced drying at lower slope positions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".