Mass transfer and bubble hydrodynamics in stirred tank with multiple properties fluid via a <scp>CFD‐PBM</scp> method
Bibliographic record
Abstract
Abstract The performance of a stirred bioreactor was evaluated in this study in terms of the bubble hydrodynamics and the mass transfer efficiency, using a non‐viscous Newtonian fluid of water, a viscous non‐Newtonian fluid of xanthan, and a viscous non‐Newtonian fluids of xanthan with dispersed soybean powder, respectively. The computational fluid dynamics–population balance model (CFD‐PBM) method coupled with the viscosity model and the mass transfer model is established to simulate the gas–liquid mass transfer process and bubble size distribution in the stirred bioreactor. The results demonstrate that the rheological properties of the fluid play an important role in determining the gas holdup, the mass transfer efficiency, and the bubble size distribution. Viscosity of the fluid exhibits a negative impact on gas–liquid mass transfer rate and gas holdup. Moreover, by properly adjusting the operating conditions such as the stirrer speed, it is possible to modulate the gas dispersion and mass transfer rate in the reactor.
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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 | 0.001 |
| 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".