Euler–Lagrange modeling of a gas–liquid stirred reactor with consideration of bubble breakage and coalescence
Bibliographic record
Abstract
Abstract Simulations of a gas–liquid stirred reactor including bubble breakage and coalescence were performed. The filtered conservation equations for the liquid phase were discretized using a lattice‐Boltzmann scheme. A Lagrangian approach with a bubble parcel concept was used for the dispersed gas phase. Bubble breakage and coalescence were modeled as stochastic events. Additional assumptions for bubble breakup modeling in an Euler–Lagrange framework were proposed. The action of the reactor components on the liquid flow field was described using an immersed boundary condition. The predicted number‐based mean diameter and long‐term averaged liquid velocity components agree qualitatively and quantitatively well with experimental data for a laboratory‐scale gas–liquid stirred reactor with dilute dispersion. Effects of the presence of bubbles, as well as the increase in the gas flow rate, on the hydrodynamics were numerically studied. The modeling technique offers an alternative engineering tool to gain detailed insights into complex industrial‐scale gas–liquid stirred reactors. © 2011 American Institute of Chemical Engineers AIChE J, 2012
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".