Fluid Dynamics Modeling of a Commercial Ebullated Bed Hydroprocessor
Bibliographic record
Abstract
A new multiphase fluid dynamics model for a commercial ebullated bed hydroprocessor was developed. The impact of the gas–liquid distribution system is now explicitly included through new submodels for bubble size distribution and drag coefficients. The size distribution submodel is coupled with the existing gas–liquid separation submodel to better predict recycled gas and liquid flow rates. Either the mass of the catalyst inventory or recycle pump curve can be specified as inputs to converge the model; the former is not always well known during operation in which case the latter can be used after making a few assumptions. A sensitivity analysis was performed to study the impact of fresh treat gas velocity, catalyst mass, phase properties, and reactor internals on recycled gas and liquid flow rates, bubble size distribution, and bed liquid holdup. A 0.2 mm shift in bubble size distribution toward larger sizes was found to significantly increase bed liquid holdup, suggesting that distributor modification/redesign could help improve the capacity of the hydroprocessor.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".