Effects of plate wear on bar forces and fiber properties in a mill scale LC-refiner
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 refiner plate wear on bar force sensor measurements. 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, force profiles for individual bar passing events (BPE) were investigated. 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 dual peak ratio and time to peak of the early peak in the dual peak events. Force measurements are evaluated over the full run time of a set of refiner plates. Findings are compared with refiner plate wear measurements and discharge fiber analysis. It is shown that the decrease in the prevalence of the corner force correlates with the wear of the leading edge of the refiner bars or bar rounding of the run time of the refiner plate. This is accompanied by a decrease in plate performance which is represented by a decrease in fiber length and freeness reduction for the same refiner load.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".