Gas recirculation rate and its influences on mass transfer in multiple impeller systems with various impeller combinations
Bibliographic record
Abstract
Abstract Both the numerical and experimental approaches were used to study the effects of the gas recirculation and non‐uniform gas loading on the mass transfer rate for each impeller in a multiple impeller system. By combining the calculated gas velocity and local gas holdup, the gas recirculation rate around each impeller was estimated. The local mass transfer coefficients for systems equipped with various combinations of the Rushton turbine impeller (R) and pitched blade impeller (P) were determined by using the dynamic gassing out method. It is found that the Rushton turbine impeller has to be served as the lowest impeller in order to have a better gas dispersion and to give a higher overall KLa for a multiple impeller gas‐liquid contactor. The upper pitched blade impeller always enforces the circulating flow around the Rushton turbine impeller just beneath it and gives a higher overall average mass transfer rate. However, the system equipped with only the pitched blade impellers results in a much lower mass transfer rate than the other systems owing to the poor gas dispersion performance of the pitched blade impeller.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".