Application Of FBG Sensors For Fatigue Monitoring Of Advanced Polymer Matrix Composites
Bibliographic record
Abstract
The utilization of polymer matrix composites (PMCs) in the aerospace industry has increased over the last decade due to their high specific strength. The next generation of PMCs has the potential of being used for applications of elevated temperature (ET). Work conducted in this thesis is aimed at developing test methodology for the characterization of fatigue behavior of PMCs at ET. Conventional strain measurement techniques (e.g. strain gages and extensometers) have limited applicability during cyclic loading. An alternative strain sensing technology is the Fiber Bragg Grating (FBG) sensor. In this thesis surface mounted and embedded FBG sensors are used to monitor stiffness degradation and damage development in woven PMCs during fatigue loading at temperatures up to 200°C. Results demonstrate the applicability of FBGs for fatigue monitoring of PMCs in this temperature range. Also, the effect of temperature on the off-axis properties of PMCs is captured and discussed.
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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".