Prediction of Failure in Unsaturated Polyester Reinforced by Plain Weave Glass Fabric
Bibliographic record
Abstract
Polyester/glass fiber is probably by far the most commonly used composite. This paper presents the results of an investigation on the failure of this composite made with a plain weave glass fabric. A recently proposed sub-plies model is utilized to predict the failure strengths of the fabric composite after shear deformation of the interlaced yarns, induced by the forming process. A procedure for the determination of the equivalent on-axis tensile and compressive strengths of the constituent plies is also proposed to take into account the fiber undulation effect on strength performance. The predicted compressive and tensile strengths are compared with experimental measurement as a function of the deformation angle of the interlaced yarns. Furthermore, the onset of damage is also compared with the initial failure predicted by the sub-plies model. The predicted results are in good agreement with the experimental data.
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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) | 0.001 | 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".