Characterization of interfacial properties of composite materials by acoustic emission
Bibliographic record
Abstract
Abstract The global mechanical properties of composite structures in service depend on fiber/matrix interface and interlaminar strength. The paper proposes to use Acoustic Emission (AE) and advanced signal processing to evaluate the interlaminar performance of polymeric composites. A delaminating process simulated with a Double Cantilever Beam (DCB) in opening mode (Mode I) coupled with an Acoustic Emission (AE) technique has been employed. Different samples were analyzed to observe the damage evolution and to evaluate the interlaminar decohesion processes. The resistance to delamination growth is expressed in terms of the interlaminar DCB mode (mode I) fracture toughness, measured by strain energy release rate, G I , dissipated per unit area of delamination growth in composite. Three categories of samples were used: two unidirectional carbon fiber/epoxy resins with one degraded by heat and one with a commercially used resin. It was found that sample that was exposed at a temperature greater than the glass transition temperature Tg of the epoxy had a higher cumulative energy release rate than the two other samples types. The original type having the lowest release rate. Acoustic emission parameters have been found to be powerful indicators of the intensity of the damage. Multivariate analysis of up to 49 parameters was performed in order to group classes of AE signals with matching characteristics. A correlation was established between the energy release rate and the acoustic emission energy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 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".