Characterizing jamming of dilute and semi-dilute fiber suspensions in a sudden contraction and a T-junction
Bibliographic record
Abstract
The clogging or jamming of particle suspensions is a ubiquitous problem, hindering the efficiency of particle–liquid and particle–particle separations. Motivated by pressure screening in the pulp and paper industry, we characterize jamming of dilute and semi-dilute mono-disperse rigid-rod suspensions passing through channels mimicking dead-end and cross-flow filtration membranes, experimentally, using particle-tracking velocimetry. We observe that jams nucleate by either bridging of isolated particles across the constriction, or by localized mechanical entanglement of the particles, i.e., flocculation. Uniquely, we observe floc-formation during acceleration into the aperture and report this as primary mechanism for jamming events. We characterized the accumulation-release cycles of the jamming event using an exponential probability distribution; this distribution is indicative of a Poisson process. For jams nucleated by single-particle bridging, the distribution is (primarily) related to the number of fibers passing through the aperture; this is similar to dry, granular materials. For floc-based nucleation events, the distribution is (primarily) related to the suspension concentration with the average time between jams decreasing inversely with the square-root of the initial suspension concentration. For the conditions tested, the distribution was insensitive to changes in constriction geometry.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".