Mechanism and control of hierarchical granule replacement in conveyor-driven filters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Granular filters demonstrate promising dust removal capabilities. Hierarchical replacement strategies can mitigate depth-dependent clogging and sustaining performance of granular filters. This study utilizes the discrete element method (DEM) to investigate hierarchical granule replacement in conveyor-driven systems, focusing on the effect of conveyor velocity v and inclination θ, and outlet size D on the hierarchical replacement degree λ. Upstream granule replacement dominance (λ > 0) when both D and θ are relatively small, while downstream granule replacement dominance (λ < 0) when D and θ are comparatively large. v exhibits no discernible impact on the hierarchical replacement degree. The inclination angle θ modulates effective friction coefficient between the granules and conveyor belt to change the hierarchical replacement degree. Hierarchical granule replacement arises from two competing transport mechanisms: shear-driven upstream flow and arch-mediated downstream discharge. The upstream flow is mobilized by frictional shear stress. The downstream flow is intermittently blocked by the force arch, whose collapse triggers “avalanche” cascades, larger D destabilizes arches, accelerating downstream granules cascades. This work establishes a predictive framework for optimizing hierarchical replacement in granular dust-removal beds and informs the design of advanced granular material systems.
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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 | 0.001 |
| 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 it