Fracture characterization of bonded composites: A comparative study
Bibliographic record
Abstract
Bonded joints have important benefits over conventional joining techniques such as rivets, welding, bolts and nuts in structural applications, particularly for components prepared of composite or polymeric materials. Due to the involvement of many geometric, material and construction variables, and the complex fracture and mechanical modes offered in the bonded joints, a proper consideration of fracture behavior is required to fully achieve their benefits. The fractures in bonded joints are mainly of three types; interlaminar (delamination), adhesive (interfacial) and cohesive crack. For a particular defect, crack propagation may occur in the tensile (mode I), the shear (mode II), and the tear (mode III) and their combinations (mixed mode). This study deals with topics such as theories of bonded composite joints and repairs, finite element analysis and fracture-based analysis and tests of mixed-mode cohesive, interfacial and interlaminar fracture mechanics. By employing geometrical factors extracted from finite element analysis and experimental results obtained from a modified Arcan test fixture, the mixed-mode cohesive, interfacial, and interlaminar fracture toughness are determined and fracture surfaces obtained are discussed.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".