Fatigue life prediction of hybrid carbon-flax-epoxy laminates using progressive failure analysis and cohesive zone model
Bibliographic record
Abstract
A 3D progressive fatigue damage model was incorporated into ABAQUS software to predict the fatigue life of hybrid carbon-flax-epoxy composites. A cohesive zone method was employed to simulate delamination damage at carbon/flax interface. To evaluate the accuracy of the finite element model, two different layups, namely, unidirectional [0–90 C2 /0 F6 ] S (UD) and angle-ply [0–90 C2 /(±45) F6 ] S (AP), consisting of 12 flax fibers layers (F) sandwiched between four woven carbon fibers layers (C) were created using hand lay-up technique and then placed in compression molding. There is a good agreement between experimental and predicted fatigue life. It was observed that the predicted fatigue life is reduced by about 14% by changing the void content from 0.38% to 3.83%. The finite element analysis revealed that the matrix in the flax region of the AP layup failed at 12% of fatigue life, followed by delamination at the carbon/flax interface, consistent with SEM results.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".