Experimental Study and Surface Deposition Modelling of Amended Oil Sands Tailings Products
Bibliographic record
Abstract
Recent pilots on emerging oil sands tailings technologies have confirmed that deposit thickness is an important parameter controlling tailings dewatering, and a key parameter governing cost.Controlling or managing deposit thickness continues to be an important challenge for full-scale implementation of tailings technologies that exhibit a yield stress.From the perspective of deterministic modelling of such deposits, there are many challenges, including measurement of the relevant rheological parameters, and how to handle time-variant rheology when modelling.This research characterizes the rheology of a mineral slurry with relatively high clay content, which is treated with a high molecular weight anionic polymer to induce flocculation.Rheometry results showed that while flocs break down under high shear, flocs reform at lower shear rates.Breakdown and recovery of flocs was confirmed by measuring the shear modulus under dynamic loading and a set of microstructural analysis.Moreover, it was shown that the tailings manifest viscosity bifurcation behaviour similar to pure clay, including shear history dependent apparent yield stress.The measured rheology was then modeled using a previously published viscosity bifurcation model that accounts for hysteresis in the apparent yield stress.The rheology results are used semi-quantitatively to explain deposition rate dependent behaviour seen in flume tests.The geometry of tailings in flume tests with relatively slow deposition is affected by the behaviour of earliest deposited tailings, which appear to have iii recovered structure sufficiently to manifest a large yield stress.This yield stress is much larger than the yield stress exhibited by tailings when they initially come to rest.This full recovery of the yield stress seems to be particularly important to managing surface deposition, as zones of tailings that have stopped moving substantially steepen the slope of deposits near the deposition point.Finally, and using the rheological models obtained, an attempt was made to model such flows at bench and pilot scales using 3D/2D numerical simulations.The flume test and field deposition conducted were simulated using CFX.It is found that using the lower limit yield stress value and by conducting simulation in several stages (to account for ageing behaviour), more realistic results could be obtained.iv
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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".