Interpretation of force profiles in mill-scale LC refining
Bibliographic record
Abstract
Abstract A set of piezo electric force sensors is implemented in a 52-inch mill-scale low consistency refiner to explore the effect of varying operating conditions on bar force profiles. The sensor replaces a short length of a stator bar and measures normal and shear forces applied during the passage of each rotor bar. In previous work with this type of force sensor a rotary encoder was used to investigate force profiles for individual bar passing events (BPE) on a 16-inch laboratory-scale refiner. In the work presented here, force profiles for individual BPEs are identified based on key features in the time domain force data. The individual bar force profiles are classified as single peak events which feature one peak corresponding to the fiber compression force and as dual peak events corresponding to fiber compression force and the corner force . The bar passing events are then analysed based on their mean force profiles and their dual peak ratio in the bar passing event. Findings are compared and validated by previous work on bar force profiles. It is shown that dual peak events which are considered to represent the corner force, are present through out the whole range of refining and increase with increased refining energy. This increases the understanding of the way corner force contributes to the refining process. Furthermore, it is found that different radial positions on the stator plate are subjected to different force profiles. This is thought to be due to the difference in tangential speed and a change in the fiber and floc material properties at different radial positions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".