Development of Creep Test Method for Thermoplastic Fiber-Reinforced Polymer Composite Tubes Under Pure Hoop Loading Condition
Bibliographic record
Abstract
Abstract Piping made from thermoplastic fiber reinforced polymer composites (TP-FRPCs) is receiving increasing attention in the oil and gas industry. Creep and time-dependent behavior is one of the main factors defining the service life of TP-FRPC structures. The lifetime and time-dependent behavior of TP-FRPC structures can be predicted using simulation tools, such as finite element analysis, to aid in the design optimization by modeling the long-term behavior of the material. Composite material time-dependent properties are required inputs for such models. While there is previous research available on creep testing of TP-FRPCs in laminate geometry, such tests may not enable accurate determination of the composite properties due to edge effects. On the other hand, coupons with tubular geometry not only provide improved load distribution between the fibers and matrix with minimal end effects, they also enable certain loading conditions experienced during typical piping operations such as internal pressure. In this study, a testing method to capture the creep behavior of tubular TP-FRPC specimens subjected to multi-axial loading conditions was developed. Tubular coupons were prototyped by an automated tape placement process. Strain was measure using digital image correlation technique and strain gauges. The development of the test setup forms the foundation for further testing of tubular TP-FRPC coupons at different multi-axial loading conditions. As a preliminary test, the creep behavior of a TP-FRPC tube subjected to pure hoop stress condition was evaluated using the developed testing process.
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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 | 0.001 | 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".