Internal Notched Flexure (INF) Test for Measurement of Mode II Interlaminar Fracture Toughness of Fiber Composites
Bibliographic record
Abstract
Abstract A revised analysis to derive the expression for the mode II interlaminar fracture toughness of fiber-reinforced polymers from internal notched flexure (INF) testing in small deformation is presented here. The approach adopted for the derivation takes into account the interlaminar shear load in the overhanging section outside the span. This improves the prediction accuracy for the initial specimen compliance, as evident from a finite element (FE) model of the INF specimen. The FE model also suggests that extensive damage develops at the crack tip before the delamination growth. Therefore, rather than using the physical crack length to calculate the interlaminar fracture toughness, one should use the effective crack length, which can be determined based on the measured specimen stiffness from experimental testing. With that, the analytical expression yields an inerlaminar fracture toughness that is consistent with the input value for the cohesive elements of the FE model.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".