Numerical investigation of flow, heat transfer, and kinetic reaction in a large‐difference bidisperse, circulating fluidized‐bed reactor
Bibliographic record
Abstract
Abstract To study particle bidispersity effect on the comprehensive performance of a gas–solid fluidized system, multi‐field coupling numerical research of large‐difference bidisperse circulating fluidized bed was performed. First, numerical simulation was conducted on the dynamic characteristic of a bidisperse gas–solid system that contained both Geldart A and B particles; heat transfer and reaction performances were then studied with the introduction of a propane dehydrogenation (PDH) kinetic reaction model; and finally, the concept of coupling fluid catalytic cracking (FCC) and PDH processes was proposed, and the feasibility was preliminarily discussed. The results showed that the two particle phases were hierarchically distributed with a pronounced segregation layer due to their large‐difference bidispersity characteristic, the Geldart B‐type particle was in a bubbling fluidizing state, while the Geldart A‐type particle was in a turbulent fluidizing state. With the initialized bed and regeneration temperature set to 973 K, the regenerated catalyst's final, balanced temperature could decrease to 942 K, which demonstrated that a significant decline in contact temperature between the feedstock and catalyst could be achieved in the following FCC risers. Additionally, this coupling process also achieved a nearly complete conversion of propane into propene, with a conversion efficiency of above 95%. The results showed the feasibility of this coupling process, which could optimize FCC riser reaction conditions and further achieve a higher‐valued light gas yield. This research can provide a reference for the study of the bidispersity effect on a gas–solid system, and the introduced coupling process can provide a new model for the FCC process's optimization.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".