Effect of Change in Fluidizing Gas on Riser Hydrodynamics and Evaluation of Scaling Laws
Bibliographic record
Abstract
Riser hydrodynamics in a circulating fluidized bed are investigated experimentally and numerically by changing the composition of the fluidizing gas. Helium gas is added to air in the range of 0 to 96 vol % for fluidizing FCC particles 78 μm in size and density of 1560 kg/m 3 . Increasing He concentration decreases the fluidizing gas density and viscosity. The effect of change in gas composition is measured through the change in voidage along the riser from the pressure drop and the solids circulation rate, while analyzed by changes in slip velocity and particle Reynolds number. Numerical simulations using Computational Fluid Dynamics (CFD) have successfully predicted the experimental measurements over the entire range of fluidizing gas densities investigated. Simulations have also revealed that interphase momentum exchange in the bottom, accelerated region of the riser is dominated by cluster formation, while individual particle drag was dominant in the upper, more dilute regions. Given that CFD simulations have successfully reproduced these results, a scaling scheme is investigated whereby a hot model unit is simulated keeping either the Archimedes number or the density ratio of particle to gas constant. The results indicated better agreement between experimental and numerical voidage profiles for the density ratio scaling. Using the full set of scaling laws produced excellent prediction of the upper, fully developed region of the riser, but failed in the bottom regions. The scaling error in the bottom region was attributed to the momentum interaction in this region being dominated by cluster formation and not by the drag force on individual particles for which the scaling laws were derived. CFD has shown to be an effective tool in evaluation of scaling laws in risers.
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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 | 0.004 | 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 | 0.001 |
| 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".