Assessing the Erosion Corrosion Properties of Materials for Slurry Transportation and Processing in the Oil Sands Industry
Bibliographic record
Abstract
Abstract Two approaches are being utilized to assess a range of materials for service in erosion-corrosion (E-C) conditions that occur during processing and transportation of aqueous slurries in oil sands operation. These are (1) using a custom-built slurry pot erosion-corrosion (SPEC) evaluation system and (2) compiling E-C maps using data from separate slurry erosion and static corrosion tests. Using slurries containing 3.5wt% NaCl solution and 20wt% silica sand, the SPEC system confirmed that bi-metallic high Cr steel pipe product and WC/Stellite 21 PTAW overlay have provided the highest erosion-corrosion resistance of materials tested to date. The E-C maps confirmed that Stellite Co-based alloys exhibited the superior corrosion resistance whilst WC-based overlays produced the best erosion resistance of the material classes evaluated. Despite having certain limitations, both approaches provide satisfactory means of assessing materials in erosion-corrosion environments. Test conditions for both systems can be tailored to simulate particular industrial operations.
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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 | 0.001 | 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) | 0.001 | 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".