Sulfur concrete for haul road construction at Suncor oil sands mines
Bibliographic record
Abstract
The feasibility of constructing mine roads at oil sands mines (Fort McMurray, Alberta) using concrete prepared from bitumen extraction and upgrading by-products and mine wastes (sulfur, fly ash, coke, and tailing sand) is evaluated. An extensive laboratory test program, including unconfined compression testing, sonic velocity measurement, and split tensile and freeze–thaw durability tests, was carried out to characterize the physical and mechanical properties of different mix designs of sulfur concrete. A study of the geochemical interaction of sulfur concrete with the near-surface environment included short-term interaction of surface-exposed sulfur concrete during the construction and operational life of the haul road and long-term interaction of sulfur concrete with groundwater following its eventual burial with mine wastes in the mined-out pits. Haul road test sections were designed based on the critical strain and resilient modulus design method. Stress and strain distributions in the selected haul road cross section induced by the truck tires were calculated using finite element analysis. Required pavement layer thicknesses were then determined on the basis of the truck loads, and resilient modulus and strength of the sulfur concrete and subgrade material using the critical strain and resilient modulus design method.Key words: sulfur concrete, mine haul road design, concrete pavement.
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 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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".