Gas Holdup Distribution in a Coaxial Mixer Containing Yield-Pseudoplastic Fluids: Effect of Biopolymer Concentration
Bibliographic record
Abstract
The performance of gas-liquid mixing processes in agitated vessels is commonly measured by the degree of gas dispersion, and local measurements of this parameter can provide a more accurate description of the mixing, especially for non-Newtonian fluids. For instance, the fluid flow of complex yield-pseudoplastic solutions is highly affected by the local shear stress, leading to a non-homogeneous air distribution throughout the mixing vessel. Coaxial mixers have demonstrated energy-efficient characteristics for non-Newtonian fluids that improve mixing homogeneity due to the independent rotation of a central impeller and a close-clearance impeller. Therefore, this work aims to investigate the axial profile of the local gas holdup in a PBT-anchor coaxial mixer containing xanthan gum solutions, which is a biopolymer widely utilized as an emulsion stabilizer, dispersing agent, and thickener. The rheological behavior of the solutions was described by the Herschel-Bulkley model, and the effect of the xanthan gum concentration on the gas holdup distribution was analyzed. Electrical resistance tomography (ERT) was employed to obtain the gas holdup from the conductivity measurements of the mixture in each of the four horizontal planes. Results show that the gas holdup increased downward for all solutions, and a lower xanthan gum concentration reduced the non-homogeneity in gas distribution and the overall gas volume fraction. In contrast, higher xanthan gum concentrations enhanced gas holdup in high shear stress regions while weakening air dispersion distant from those regions due to higher viscous forces.
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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".