The influence of UV radiation on the properties of GFRP laminates in underwater conditions
Bibliographic record
Abstract
Degradation of polymer composites is a significant problem in many engineering aspects. Due to the interaction of various degradation factors during the exploitation of composites, a synergistic effect of destruction is observed. The article describes the phenomena occurring in glass fiber reinforced polyester laminates under the influence of ultraviolet radiation (UV) in an aquatic environment. The laminates were exposed to UV-A, UV-B and UV-C radiation for 1000 h in free-air and underwater conditions. During the test, the materials were immersed at stable depth of 1 mm and 10 mm, respectively. The three-point bending tests performed on the samples after being exposed to UV showed an increase in the flexural strength of the composites. Simultaneously, degradation of the outer surface layer was observed. The degradation removed the thin resin film from the surface which resulted in a direct exposure of the reinforcing fibers to the environment. The transformations taking place in the deeper layers of the composite increased the mechanical strength due to the additional cross-linking reactions excited by the energy arising from the radiation. Moreover, the formation of polymer structures from free styrene remaining after the technological process and the occurrence of free radical reactions as a result of the cage effect was also observed.
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 | 0.000 |
| 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".