U-shape core-offset fiber sensor with submicrostrain resolution over a 35 millistrain range
Bibliographic record
Abstract
Large strain with submicro resolution is essential for steel structural monitoring; however, the fiber base sensors are limited by the glass extension to be less than 1%. Here, we propose a U-shape core-offset fiber sensor including four fiber segments to realize a large strain sensor. Four fiber segments with slight length differences in between are core-offset fused together to achieve U-shape spring-like microstructure fiber for large transverse bending radius. The reflected high-order modes at three silica/air interfaces interfere to give a broad spectrum due to unequal segment length, which enables continuous strain detection over 35 mɛ. The air and glass hybrid structure of the device enables the large bending, and hence compression and tension measurement can be achieved simultaneously. The strain sensitivity is up to 20.75 pm/µɛ with the strain accuracy of 0.5 µɛ. This novel, to the best of our knowledge, core-offset fiber has high strain sensitivity and large strain range for compression and tension strain measurement. Furthermore, the proposed strain sensor can be fabricated easily for practical applications where large strain with high strain accuracy is needed.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".