Bubbles in a sand fluidized bed unit for the gasification of coffee waste biomass. A probabilistic based fluid‐dynamic description
Bibliographic record
Abstract
Abstract The present study shows the applicability of the chemical reactor engineering centre (CREC) Optiprobes engineered with a graded refractive index (GRIN) lens and fibreoptics to establish both the bubble rising velocity (BRV) and the bubble axial chord (BAC) of bubbles in a 240–955 μm sand fluidized bed, filled with different types and loadings of biomasses. It is confirmed via the application of the CREC Optiprobes that the formed bubbles display both BRV and BAC normal probabilistic distributions, leading to characteristic BRV–BAC bands of bubble behaviour, with this being true for an ample range of superficial gas velocities (0.188–0.282 m/s) and broza biomass loadings (0–30 vol.%). It is also proven that the observed BRV and BAC distributions in biomass‐loaded sand fluidized beds are of the quasi‐normal distribution type, as attested by the Shapiro–Wilk test (S–W test). Furthermore, a probabilistic prediction model (PPM) proposed in a previous contribution can be used effectively to predict, in all cases, that a close to 80% of the total bubble population falls within a proposed probabilistic band of bubble behaviour.
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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) | 0.000 | 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 | 0.000 |
| 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 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".