Phase distributions in a gas–liquid–solid circulating fluidized bed riser
Bibliographic record
Abstract
Abstract The distributions of the three phases in gas–liquid–solid circulating fluidized beds (GLSCFB) were studied using a novel measurement technique that combines electrical resistance tomography (ERT) and optical fibre probe. The introduction of gas into a liquid–solid circulating fluidized bed (LSCFB), thus forming a GLSCFB, caused the increase of solids holdup due to the significantly decreased available buoyancy with the lower density of the gas, even with a somewhat increased liquid velocity due to the decreased liquid holdup giving space for the gas holdup. The gas passed through the riser in the form of bubbles, which tended to flow more through the central region of the riser, leading to more radial non‐uniformity in radial holdup of the phases. The gas velocity has the most significant effect on the gas phase holdup. While the gas velocity also has an obvious effect to the solids holdups, the liquid flow rate had a much more considerable effect on the phase holdups. The solids circulation rate also had a significant effect on the phase holdups, with increasing solids circulation rate causing much more increased solids holdup in the central region than close to the wall. A correlation was developed for the relative radial distributions of solids holdup in GLSCFB, as such radial profiles were found similar over a wide range of operating conditions, like those in a typical gas–solid circulating fluidized beds (GSCFB). Finally, the axial solids profiles in a GLSCFB was found to be much closer to those in an LSCFB which are very uniform, than those found in a GSCFB which are less uniform and sometime having a S shape. Water was used as the continuous and conductive phase, air was the gas phase and glass bead and lava rock particles were used as the solid and non‐conductive phase.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".