Spanning the flow regimes: Generic fluidized‐bed reactor model
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Probabilistic averaging is used to model fluidized‐bed reactors across the three fluidlization flow regimes most commonly encountered in industry (bubbling, turbulent, and fast fluidization), extending earlier work, which introduced this approach to bridge the bubbling and turbulent regimes of fluidization. In extending this concept to the fast fluidization regime, the probabilities of being in each of the three regimes are represented as probability density functions derived from regime boundary transition data. The three regime‐specific models—a generalized version of a two‐phase bubbling bed model at low gas velocities, a dispersed flow model for turbulent beds at intermediate velocities, and a generalized version of a core‐annulus model at higher velocities—are employed, leading to improved predictions compared with any of the individual models, while avoiding discontinuities at the regime boundaries. Predictions from the new integrated model are in good agreement with available ozone decomposition data over the full range of applicability covered elsewhere.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it