Multi‐scale CFD simulation of operating diagram for gas–solid risers
Bibliographic record
Abstract
Abstract Our recently presented multi‐scale computational fluid dynamics (CFD) approach has proven to be able to capture the choking phenomena in a circulating fluidized bed (CFB). However, how to transfer this capability to assist industrial operation remains to be explored. To this end, this paper presents further simulation results over the intrinsic flow regime diagram and the operating diagram for gas–solid risers, showing the variation of flow regimes with gas velocity and solids flux as well as riser height. It is confirmed that the choking in CFB risers, characterized by the saturation carrying capacity and the coexistence of both dense and dilute flows, holds clear‐cut definition in hydrodynamics. In physics, both the choking, non‐choking transitions, and the critical point in‐between are intrinsic nature of gas–solid riser flows; they initiate as functions of gas velocity and solids flux. In engineering operation, however, their appearances vary with the riser height used. As a result, the intrinsic flow regime diagram can be defined by the combination of gas velocity and solids flux, although it is hard to obtain in practice owing to the limitation of riser height. The operating diagram of a CFB should be, accordingly, height‐dependent in practice, demanding the riser height as a parameter besides commonly believed gas velocity and solids flux.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".