Prediction of spout diameter in gas‐solid spouted beds using factorial design of experiments approach with the aid of advanced optical fibre probe
Bibliographic record
Abstract
ABSTRACT In this study, the effects of five operating and design variables (solid density, static bed height, particle diameter, superficial gas velocity, and inlet diameter) on the average spout diameter of a 0.152 m inside diameter gas‐solid spouted bed have been assessed experimentally using advanced gas‐solid optical fibre probe technique. Statistical analysis of the experimental data including the factorial design of the experiments using MINITAB17 statistical software has been performed to determine the extent of the effects of these variables on the spout diameter as a case study. It was found that all five operating and design variables, except the solid density together with the 2‐ways interactions between particles size and inlet diameter, in addition to gas velocity and inlet diameter, have a significant effect on the average spout diameter. Regression analysis was performed to correlate these variables with the average spout diameter for the gas‐solid spouted beds. The obtained preliminary regression correlation was able to closely predict the average spout diameter of this work with the mean relative deviation value of 0.7 %.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".