Industrial application of ceramic nanofiltration membranes for water treatment in oil sands mines
Bibliographic record
Abstract
A commercial titania ceramic nanofiltration membrane unit with a permeate flow capacity of 20 m3/h was used to reduce ion concentration, Total Suspended Solids (TSS) and Total Organic Carbon (TOC) in recycle water from a Canadian oil sands mine. This unit, the first of its kind, was tested for almost two years to evaluate membrane performance under actual recycle process water conditions. This paper focuses on the results at a 50% stage cut. A strong correlation between specific flux and rejection was found, with the highest mass rejections observed at the lowest specific flux values. A potential formation of a cake layer on the membrane surface seems to favour the rejection since lower specific flux values improved mass rejection. The analysis of more than 20 ions showed that differences in hydrated ionic sizes and electrostatic phenomena are at play with divalent cations showing the largest rejection. Additional 75–90% TOC and almost 100% TSS rejection was observed. These results indicate that it is possible to implement this technology in an oil sands mine and obtain significant water quality improvements and reducing river water intake.
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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 | 0.000 |
| 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 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".