In‐line jet mixing of liquid‐pulp‐fiber suspensions: Effect of fiber properties, flow regime, and jet penetration
Bibliographic record
Abstract
Mixing effectiveness was determined experimentally for side jet injection into pipe flow for water and pulp suspensions for a range of fiber mass concentrations (0–3.0%), mainstream velocities (0.5–5.0 m/s), and side‐stream velocities (1.0–12.7 m/s). The mixing quality was measured in cross‐sectional planes along the pipe using electrical resistance tomography and quantified by a modified mixing index, derived from the coefficient of variation of conductivity. Mixing depended strongly on the flow regime and jet penetration. For turbulent flow, the criteria for in‐line jet mixing in water are applicable to the mixing in suspensions, with small differences likely due to differences in fiber network strength and influences of fiber‐turbulence interactions in modifying turbulent structures in the bulk. When a suspension flows as a plug, however, the mixing differs greatly from that in water, depending on the fiber network strength in the core of the pipe. © 2012 American Institute of Chemical Engineers AIChE J, 59: 1420–1430, 2013
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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 | 0.000 |
| 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".