Bibliographic record
Abstract
Fiber optic sensors are designed to measure various parameters. The distributed fiber optics sensor has been a very promising candidate for the structural health monitoring. In this thesis, we characterized LEAF (Large Effective Area Fiber) fiber’s Brillouin scattering spectrum and investigated its potentiality for the distributed Brillouin temperature and strain sensor. Optical fibers with complex refractive index profiles are applied to improve the Brillouin threshold by varying the Brillouin linewidth. As LEAF fiber has a modified refractive index profile, we investigated its Brillouin linewidth’s dependence on the square of the pump light’s frequency. We verified the Brillouin frequency’s variation with input SOP experimentally for LEAF fiber in the spontaneous regime. This sets a limitation for the frequency resolution of distributed Brillouin sensors. We also realized a simultaneous temperature and strain sensor with LEAF fiber applying the Brillouin optical time domain analysis. Based on the direct detection of LEAF beat frequencies, a simultaneous strain and temperature sensor was demonstrated.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".