Mixing Characteristics of an Axial-Flow Rotor: Experimental and Numerical Study
Bibliographic record
Abstract
In the metallurgical industry, various types of rotors are used for the injection and distribution of gas and for homogenizing molten metal. In the present work, the liquid-gas two-phase flow around an axial type impeller is studied in a water model, in order to analyze the bubble break-up and coalescence and metal mixing. Details like primary and secondary vortex structure, gas flooding between the blades and gas dispersion are recorded by using high speed photography.A mathematical model that takes into account the combined effect of bubble break-up and coalescence is implemented in the commercial computational fluid dynamics (CFD) software FLUENT. In the proposed work, the impeller is explicitly described in three dimensions using Multiple Reference Frame Model. Dispersed gas and bubbles dynamics in the turbulent water are modeled using an Eulerian-Eulerian approach with dispersed k-epsilon turbulent model. The model predicts spatial distribution of gas hold-up, average bubble size and flow structure. Good qualitative agreement between physical model and simulation is achieved when comparing the bubble size distribution, flow structure and mixing.
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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".