Combined compression-tension strain sensor over 1 µε–20 mε by using non-uniform multiple-core-offset fiber
Bibliographic record
Abstract
Combined compression-tension strain sensors with a range of 1 micro to a maximum of 20 milli-strain based on non-uniform multiple-core-offset fibers have been realized. A large strain range with high resolution is ideal for monitoring deformation of steel structures where a large compressive and tensile strain co-exists. Thanks to core-offset splicing of non-uniform fiber segments, unique asymmetric waveguides reduce the degeneracy of each section, realizing a reflection spectrum with a large range and irregular shape. Furthermore, enhanced multi-mode interference induced from high-order modes in silica cladding and air results in the large strain range with high resolution in both compression and tension regions. The sensitivity of 7.93 pm/µ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mtext>ε</mml:mtext> </mml:math> with a strain step of 1.7 µ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mtext>ε</mml:mtext> </mml:math> is achieved for micro-strain measurement. For milli-strain measurement, a strain coefficient of 1.298 nm/m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mtext>ε</mml:mtext> </mml:math> over a tensile strain of 13.2 m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mtext>ε</mml:mtext> </mml:math> is realized; in the compressive strain case, a coefficient of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo>−</mml:mo> </mml:mrow> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mn>1.251</mml:mn> </mml:mrow> <mml:mspace width="thickmathspace"/> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mi mathvariant="normal">n</mml:mi> <mml:mi mathvariant="normal">m</mml:mi> <mml:mrow class="MJX-TeXAtom-ORD"> <mml:mo>/</mml:mo> </mml:mrow> <mml:mi mathvariant="normal">m</mml:mi> </mml:mrow> <mml:mtext>ε</mml:mtext> </mml:math> over compression of 20.1 m <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" display="inline"> <mml:mtext>ε</mml:mtext> </mml:math> is observed.
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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".