Material characterisation for natural fibres: compressibility, permeability and friction
Bibliographic record
Abstract
Abstract Although fibrous suspensions are finding increasing use in many applications, holistic studies investigating their material properties are essentially non-existent due to a lack of simple and reliable measurement techniques. To address this, geotechnical techniques have been considered for the characterisation of an extruded suspension of poplar fibres. Use of such characterization techniques was thought suitable since the extruded fibres share many physical similarities with fibrous peats, and since both materials are primarily derived from plants. In the present study, oedometer and direct shear tests were employed to evaluate the compressibility, permeability and friction properties of poplar fibres. Triplicates of each test were carried out for two differently prepared poplar fibres at several different initial water contents. All measurements were found to be in good agreement with the values typical of fibrous peats, justifying direct cross-over of geotechnical techniques as an alternative method for characterising and modelling fibrous suspensions in manufacturing applications.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".