Oxygen mass transfer coefficient in bubble column slurry reactor with ultrafine suspended particles and neural network prediction
Bibliographic record
Abstract
Abstract The gas–liquid volumetric mass transfer coefficient was determined by the dynamic oxygen absorption technique using a polarographic dissolved oxygen probe and the gas–liquid interfacial area was measured using dual‐tip conductivity probes in a bubble column slurry reactor at ambient temperature and normal pressure. The solid particles used were ultrafine hollow glass microspheres with a mean diameter of 8.624 µm. The effects of various axial locations (height–diameter ratio = 1–12), superficial gas velocity (uG = 0.011–0.085 m/s) and solid concentration (εS = 0–30 wt.%) on the gas–liquid volumetric mass transfer coefficient kLaL and liquid‐side mass transfer coefficient kL were discussed in detail in the range of operating variables investigated. Empirical correlations by dimensional analysis were obtained and feed‐forward back propagation neural network models were employed to predict the gas–liquid volumetric mass transfer coefficient and liquid‐side mass transfer coefficient for an air–water–hollow glass microspheres system in a commercial‐scale bubble column slurry reactor. © 2012 Canadian Society for Chemical Engineering
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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 | 0.000 | 0.001 |
| 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 | 0.001 | 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 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".