Study on flow fields in a bioreactor with perforated blades
Bibliographic record
Abstract
Abstract Flow fields of a gas–liquid fluid in a bioreactor with perforated blades were evaluated with the computational fluid dynamics and particle image velocimetry (PIV). The flow pattern of the fluid was the complex turbulence, and the fluid had preferable flow fields for fermentations. Using a rotating coordinate system and a sliding mesh method, a mesh of 24 × 16 × 80 (X × Y × Z) was selected due to its high accuracy and appropriate workload. The numerical results of the two‐phase flow model agreed well with the experimental results of the PIV, such as flow field characteristics and data curves. The RNG k–ε model was adopted, which could precisely simulate anisotropic flow fields around higher‐speed blades. Whole deviations of X‐, Y‐ and Z‐direction velocities ranged only from 5.4% to 10.5%, and continuous turbulence models could effectively simulate transfer procedures of the fluid. Because of its low cost, simplicity and easy of scale‐up, the bioreactor with perforated blades and its models mechanism of fluid microelements are expected to be efficient for its industrial amplification and application in food industry. © 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".