Study on flow microstructure and scale‐up effect in circulating fluidized bed riser using solids concentration signals
Bibliographic record
Abstract
Abstract The dynamic microstructure in circulating fluidized beds (CFBs) is complex due to particle aggregation and particle–wall interactions. Based on the local solids concentration time series from a twin–riser CFB system of 10 m high and 76.2 mm (3 in.) and 203 mm (8 in.) id with FCC particles (dp = 67 μm, ρp = 1,500 kg/m3), the dynamic microstructure and scale‐up effect were studied using nonlinear chaos analysis after an improved denoising signal process. The analysis shows that for the local solids concentration time series in the whole riser, the solids concentrations in the larger (8 in.) riser are higher and have higher fluctuation frequency than those in the 3‐in. riser. The pressure drops at the various axial levels of the 8‐in. riser are higher than the 3‐in. riser. Correlation dimension and Kolmogorov entropy in the 8‐in. riser are also higher than those in the 3‐in. riser under the identical condition. The microstructure of the gas–particle flow in the 8‐in. riser appears to be more complex than that in the 3‐in. riser at identical axial levels and under the same solids flux and superficial gas velocity. In the larger riser, the energy distribution in wavelet domain is also stronger than that in the 3‐in. riser. Clearly, the scale‐up effect is very notable in CFB reactors, not only on the macroscale level but also on the microscale level. Such effect should be considered during designing and operating commercial size CFB reactors.
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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 | 0.001 | 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".