CFD simulation of solids residence time distribution for scaling up gas‐solid bubbling fluidized bed reactors based on the modified structure‐based drag model
Bibliographic record
Abstract
Abstract Solids residence time distribution (RTD), which reflects the degree of solids mixing in bubbling fluidized bed (BFB), has become an essential parameter for the evaluation of reactor performances. In this paper, a modified structure‐based drag model was established to investigate the effect of the bed size and the correlation of bubble dimension on the gas‐solids hydrodynamics and solids RTD in three different scales of BFB. The result obtained from the modified structure‐based drag model shows better agreement with the experimental values and it can be used to predict the RTD properly. The deviation of flow field will cause a large difference in the RTD prediction. An accurate flow field is a prerequisite for calculating the RTD. For the cases of Geldart B particles, the Darton correlation is the best choice for low gas velocities. When scaling up a BFB, the RTD calculated by the modified structure‐based drag model is reduced in comparison with the experimental value, which is related to the increase of the bed size and the excessive estimation of the bubble size. On the other hand, the lack of consideration for the friction on both front and back walls in 2D simulation may lead to the over‐prediction of particle velocity and result in the deviation between calculated and experimental RTD value.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| 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 teacher head, 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".