Fabrication and experimental evaluation of vibration and damping in multiscale graphene/fiberglass/epoxy composites
Bibliographic record
Abstract
In this paper, the vibration and damping properties of multiscale laminated fiberglass/epoxy composites modified with a wide range of carbon nanofillers, including multiwalled carbon nanotubes, graphene oxide, reduced-graphene oxide and graphene nanoplatelets were examined for use in structural vibration applications. Simultaneous reinforcement of matrix and fibers was carried out via a novel method that combines a nanoparticle spraying process with nanoparticle/epoxy mixture to incorporate nanoparticles for the enhancement of vibration and damping properties of multiscale laminated fiberglass/epoxy composites. The vibration and damping properties as well as morphological, mechanical properties of the glass fiber-reinforced multiscale composites were investigated. Using a forced vibration technique, the frequency-response functions, natural frequencies and damping ratios of the nanocomposites were measured. The experimental results revealed that the damped natural frequencies of the nanocomposites increased with an increase in nanoparticle concentration. However, at higher contents of nanoparticles, the damped natural frequencies decreased and the damping ratio increased.
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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 | 0.000 | 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".