Simulation of binary particle segregation for bubbling fluidized beds using polydispersed structure‐based drag model extended from a monodispersed model
Bibliographic record
Abstract
Abstract A bubble structure‐based drag model developed for the monodispersed system has been extended to simulate bi‐dispersed bubbling fluidized beds. Both dense phase and dilute phase are considered to be comprised of two types of particles with different sizes. The derivation of the structure‐based drag coefficient for individual particle based on the force equilibrium principle is proved to be independent of the volume fractions ( ε si ) of particle i. The multi‐fluid model in the commercial software Ansys Fluent is employed to evaluate the polydispersed drag model for the segregation of binary gas‐particle flows in a bubbling fluidized bed. It is shown that the simulation results predicted by the new structure‐based drag model are in reasonable agreement with experimental data with a 6.34% root mean square error (RMSE). The new structure‐based model can capture the particle distribution at the top region of the fluidized bed well. The bubble behaviour can also be captured by the new model well.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".