Assessing oil sands tailings consolidation using a modified benchtop filter press
Bibliographic record
Abstract
Open pit surface mining generates process effluents known as tailings. These mixtures accumulate in large impoundment structures typically termed as tailings ponds, which serve as storage structures where water from the tailings is separated and recycled back into the process. With the continuous accumulation of material in tailings ponds, and to comply with reclamation and water-use regulations, the industry is constantly seeking new technologies that can accelerate the tailings consolidation and dewatering process. Preliminary tools and techniques to screen potential consolidation technologies are valuable to quickly understand the effectiveness of the technology on the bench-scale before larger-scale testing. At present, settling tests have been the ideal medium for bench-scale study, however, this process can be time-intensive. This study compares a potential tool for short-term testing of consolidation, a benchtop filter press, with a standard settling test. The benchtop filter press is commonly used for the generation of specific resistance to filtration (SRF) data, however, the application for use in understanding consolidation is not. In this study, a benchtop filter press was modified to remove the limitation on the dewatering time due to the filter cake cracking, thus allowing dewatering past the liquid limit of the material. Two types of synthetic tailings were developed using a kaolinite and bentonite mix in synthetic process water, with varying solids content, methylene blue indices (MBI) and water chemistries, to mimic the conditions in actual mining samples. The study shows that the modified benchtop filter press results produce similar trends to settling tests and perform as expected with and without polymer addition. The modified benchtop filter press provides data in a course of hours to days, as compared to the settling test data that can take weeks to months to generate. Additionally, work conducted with oil sands fluid fine tailings (FFT) after various treatments, demonstrates that SRF curves from actual mining samples show trends in dewatering time consistent with observed field performance.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".