Mechanical performance of unidirectional glass fiber-reinforced thermoplastic composites under varying aging conditions
Bibliographic record
Abstract
Continuous fiber-reinforced thermoplastic composites are gaining attention in the industry due to their high toughness and recyclability, making them a promising alternative to traditional thermosetting composites for primary structural applications. However, challenges such as hydrothermal aging at elevated temperatures must be addressed before these composites can widely be adopted. Elevated temperature conditions increasingly fall within the operating range in field conditions for thermoplastic composite pipes. Although designs aim to prevent direct water exposure of the load-bearing reinforcement phase in these pipes, unexpected or accidental water ingress must be considered for safety-critical pressure piping, as it can lead to the degradation of the reinforcement material over time and eventual pipe failure. This study focuses on evaluating the mechanical resistance of unidirectional glass fiber-reinforced thermoplastic composite tapes (UGFTC) under elevated temperature and different aging conditions. Two types of thermoplastic matrices, polypropylene and polyethylene, were examined. Samples were subjected to thermal aging at 95°C and water immersion in distilled and deionized water at the same temperature for up to 4 weeks. Mechanical resistance was assessed by measuring strength reduction, with a decline of over 25% being considered severe, across the three aging conditions during this period. Water uptake behavior was also analyzed by weighing the samples over the 4-week aging period and after its completion. To further understand the damage, optical microscopy was used to compare the condition of the UGFTC samples under each aging condition. This study provides novel insights into the damaging effects on the fiber-matrix interface and the polymer matrix itself when exposed to aging in different conditions, which are key to the mechanical performance of UGFTC materials. Results indicate that samples aged in deionized water experience greater strength reduction compared to those in distilled water. Additionally, samples with polyethylene matrices show more surface damage and reinforcement degradation than those with polypropylene matrices.
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) | 0.001 | 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".