Hydrodynamic characteristics of an aerated coaxial mixing vessel equipped with a pitched blade turbine and an anchor
Bibliographic record
Abstract
Abstract Background In this work, computational fluid dynamics (CFD) simulation of an aerated coaxial mixing vessel composed of a centered impeller and a wall scraping anchor was conducted to investigate the effects of speed ratio, rotation modes (co‐rotating and counter‐rotating), and fluid viscosity on the local and global gas holdup values, flow pattern within the vessel, and turbulent kinetic energy. To validate the developed model, simulated gas holdup and gassed power uptake were compared with the measured experimental values. To gather experimental gas holdup values, an electrical resistance tomography technique was utilized. Results The results demonstrated that the co‐rotating coaxial mixer with a speed ratio higher than 10 provided a higher gas volume fraction within the vessel. It was also shown that the turbulent kinetic energy attained in the counter‐rotating mode was lower than those for the co‐rotating coaxial mixer in most regions within the mixing tank, especially near the vessel walls. The size and the number of circulation loops developed within the coaxial mixer were affected by the speed ratio. Conclusion It was demonstrated that speed ratio and rotation mode of the impellers affected the hydrodynamics developed within the aerated coaxial mixer. © 2017 Society of Chemical Industry
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| 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".