<title>Fatigue and post-fatigue performance of Fabry-Perot FOS installed on CFRP-strengthened RC-beams</title>
Bibliographic record
Abstract
There is a growing need for built-in monitoring systems for civil engineering infrastructures, due to problems such as increasing traffic loads and rising costs of maintenance and repair. Fibre optic sensors (FOS), capable of reading various parameters are promising candidates for life-long health monitoring of these structures. However, since FOS have only been introduced recently into the field of structural monitoring, their acceptance and widespread implementation will be conditioned by their durability under severe climatic and loading conditions. This paper reports on the performance of strain extrinsic FOS attached to carbon fibre reinforced polymer (CFRP) plates used to strengthen concrete structures. The specimens tested in this project are reinforced concrete (RC) beams with an additional external CFRP reinforcement. The FOS-instrumented beams were first subjected to fatigue loading for various numbers of cycles and load amplitudes. Then, they were tested monotonically to failure under four-point-bending. The test results provide an insight on the fatigue and post-fatigue behaviour of FOS used for monitoring reinforced concrete structures.
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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 | 0.000 | 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) | 0.002 | 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".