Evaluation of damage area on fibre epoxy composites using digital image processing
Bibliographic record
Abstract
In this paper, fibre epoxy composite specimens are prepared by hand lay-up method with stacking sequences (0 4 /±45 2 ) s . Five specimens are prepared with the same dimensions and named as S1, S2, S3, S4, and S5. These specimens are tested for impact analysis using a drop-weight apparatus (DWA-Ceast9350) at energy levels of 25, 30, and 35 J, followed by tensile testing using a universal testing machine (Dak9103). The damaged areas of the impacted specimens are examined by digital image processing, numerically simulated ABAQUS software, and scanning electron microscopy, followed by tensile strength results. The results of the experiment reveal that when the impact energy increases, the damage area increases, the tensile strength decreases, and the cracks formed during impact are shown in scanning electron microscope imaging. The homogeneity and isotropy of the composite are identified by the Feret ratio and circular shape factor.
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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) | 0.000 | 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".