Numerical investigation on solids settling in a non-Newtonian slurry inside a horizontal flume
Bibliographic record
Abstract
Slurry transportation is always crucial for many industrial processes. This study numerically investigates the settling behavior of multisize solid particles in a non-Newtonian slurry inside a semicircular open channel (flume). The non-Newtonian slurry is modeled using a three-dimensional unsteady Eulerian–Eulerian (E–E) model coupled with the Hershel–Bulkley rheological model. A detailed sensitivity analysis of drag models is performed to establish the solid–fluid interaction in the slurry flow. The numerical model is validated with the experimental data from the literature and shows a fair agreement. The validated model is used to simulate the settling behavior of the slurry in the flume. The mean particle diameter of the solid particles in the slurry is in the range of 75–296 μm with a median diameter of 188 μm. The effect of particle size distributions (PSDs), flume inclination, bubble size, and bubble volume fraction on the particle settling inside the flume is investigated in the parametric study. The analysis of our results revealed that the settling of solids is significantly affected by PSDs in the open channel system. In particular, the increase in flume inclination progresses the settling and dissipation of fine and coarse particles, respectively. Additional simulations showed that the inception of bubbles influences the settling velocity of solids, which changes the settling behavior of multisize solids inside the flume. The presented study can be used as a valuable guideline for the optimization of intermediate exclusion of water from thickened slurry in order to ensure the stability of tailing storage facility.
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 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 | 0.001 |
| 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) | 0.000 | 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".