The effect of discontinuous injection on particle backflow in pneumatic conveying systems
Bibliographic record
Abstract
Abstract Pneumatic conveying is used in many process industries to transport dry, granular, and powdered solids. The triboelectrification of particles during conveying causes particle agglomeration, spark discharges, and disruptions in particle flow, making particles move upstream against the fluid flow. The effect of frequency of particle injection on particle backflow is studied using CFD‐DEM simulations. Conveying flow in a square‐shaped duct with fluid frictional Reynold's number equal to 180, particle Stokes number equal to 8, and individual particle charge equal to 504 fC, is simulated with different particle injection frequencies. The proportion of particles moving upstream is found to increase as the delay period between injections increases, and the effect of the length of the injection period is minimal. Further, particles moving upstream are situated in low‐drag zones at the corners of the duct where the electrostatic force dominates. In conclusion, the delay period between discontinuous injections plays a major role in particle backflow. The findings of the article are important for industrial processes with discontinuous injection of particles with a risk of particle accumulation within the conveying boundary.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".