Measuring fibre orientation and predicting elastic properties of discontinuous long fibre thermoplastic composites
Bibliographic record
Abstract
Elastic properties in critical areas of 3 D shells made from discontinuous long fibre (DLF) composites are difficult to determine via traditional methods, due to the heterogeneity of the material and the geometry of the part. In this paper, a method is proposed to predict the local modulus of DLF composites based on a micrograph of the polished edge of a specimen. The position and orientation of each fibre are extracted from the micrograph and used in conjunction with classical lamination theory to predict the elastic modulus. Fibre discontinuity is accounted for by including a correction factor based on the Cox formula for averaged elastic constants. Model predictions successfully matched the experimental tests results. In a previous study, material flow during compression moulding of recycled DLF panels led to anisotropic behaviour, which was hypothesized to be caused by chip alignment in the flow direction. By using the proposed method, chip alignment due to flow was confirmed and the anisotropy in the elastic modulus was accurately predicted.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".