Hydrodynamics in a gravity settling vessel: CFD modelling with LDA validation
Bibliographic record
Abstract
Abstract Vertical gravity settling vessels, usually referred to as primary separation vessels (PSV), are used in separating bitumen aggregates from slurry containing sand and fine clays. The hydrodynamics in the PSV influences the separation efficiency of recovered bitumen through the overall mean flow and turbulent interaction. In order to deepen our understanding of the hydrodynamic conditions in such vessels, this paper presents a combined study of the flow field using Laser Doppler Anemometry (LDA) to measure the velocity field, and computational fluid dynamics (CFD) simulations to validate the CFD model. The investigation shows that the flow geometry has a significant influence on the overall flow pattern in such vessels. It also demonstrates that the CFD simulation is a reliable tool in capturing the complex mean flow pattern observed in experiments. Use of different turbulent models such as the standard k‐ε model and Reynolds stress model has very little effect on the mean flow field.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".