Model development for work of fracture of hybrid composites
Bibliographic record
Abstract
ABSTRACT The theoretical modeling for work of fracture of hybrid composites was investigated. Current available models for the work of fracture mostly consider single fiber composites and are not supported by experimental evidence. This is due to the complex nature of work of fracture, and presence of far too many variables for the experimental validation such as interaction of fibers with matrix and with each other. In this work, a model was developed for hybrid composites based on the modification of rule of mixtures, considering pull‐out, fracture, debonding, and stress redistribution for fibers along fracture for matrix. Later, the model was experimentally evaluated by GF‐hemp‐PP hybrid composites, and showed a better agreement in comparison to a prevalent model for work of fracture. Aside from matrix failure, the dominant failure mechanisms were fiber stress redistribution for long fiber composites and fiber pull out for short fiber composites. © 2017 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2017, 134, 44711.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".