Fines deposition dynamics in gas–liquid trickle‐flow reactors
Bibliographic record
Abstract
Abstract Nonfilterable fines, such as incipient coke particles or fines naturally occurring in oil sands bitumen, are known to be responsible for the severe plugging during the flow of (fine) solid–liquid suspensions in cocurrent gas–liquid trickle‐bed hydrotreating reactors. Accumulating fines in the porous medium causes pressure buildup, and thus the dropoff in hydrogen partial pressure in the bed, overutilizing recycling compressors and shortening the reactor operating cycles. In this work, a 1‐D transient two‐fluid hydrodynamic model based on the macroscopic volume‐average form of the multiphase system transport equations is developed, analyzed, and validated experimentally. The model hypothesizes that plugging occurs via deep‐bed filtration mechanisms. It incorporates physical effects of porosity and effective specific surface‐area changes due to the capture of fines, inertial effects of phases, and coupling effects between the fines filter rate equation and interfacial momentum exchange force terms. It is tested in the trickle‐flow regime for conditions mimicking a hydrotreating trickle‐bed process with spherical and trilobe catalysts. To rationalize deep‐bed filtration phenomena in trickle‐flow reactors, parametric studies are carried out on the effects of liquid velocity and viscosity, gas density and velocity, and fines feed concentration, on the plugging dynamics.
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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 | 0.000 |
| 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".