On two‐phase modeling of dewatering pulp suspensions
Bibliographic record
Abstract
Abstract An experimental study of the dewatering of wood‐pulp fiber suspensions by uniaxial compression is presented, to rationalize their dewatering dynamics within a two‐phase framework. Twenty‐seven pulp suspensions are examined, encompassing materials with different origins, preparation methodologies, and secondary treatments. For each suspension in this library, the network permeability and compressive yield stress are calibrated at low rates of dewatering. Faster compressions are then used to verify that a solid bulk viscosity is essential to match two‐phase model predictions with experimental observations, and to parameterize its magnitude. By comparing the results with a suspension of nylon fibers, we demonstrate that none of the wood‐pulp suspensions behave like an idealized fibrous porous medium. Nevertheless, the properties of pulp fiber networks can be reconciled within a two‐phase framework, and comparisons made between different wood‐pulp suspensions and between wood‐pulp and nylon fibers, by appealing to potential microstructural origins of their macroscopic behavior.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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 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".