Stimulated Brillouin Scattering and Longitudinal Strain Performance of BOTDA-Based Nonuniform As$_{2}$Se$_{3}$-PMMA Tapered Fibers
Bibliographic record
Abstract
Stimulated Brillouin scattering and the longitudinal strain performance based on Brillouin Optical Time Domain Analysis (BOTDA) in a 50 cm long nonuniform As$_{2}$Se$_{3}$-PMMA tapered fiber is theoretically and experimentally investigated. In the BOTDA measurement a 20 ns pump pulse is used, of which the pulse-width equivalent length is longer than the fiber under test (FUT) of 50 cm nonuniform As$_{2}$Se$_{3}$-PMMA tapered fiber. The evolution of Brillouin gain spectrum (BGS) corresponding to different fiber sections is analyzed showing the strain performance of the shift of the BGS frequency and the change of BGS linewidth under the imposed longitudinal strain. A strain-insensitive BGS linewidth is achieved by selecting the fiber gain section under the combined effects of the longitudinal acoustic velocity$V_{A}$, strain dependence of refractive index$n$, the effective fiber length$L_{eff}$and also the pump intensity$I$along the nonuniform As$_{2}$Se$_{3}$-PMMA tapered fiber. The proposed method has the potential for many novel applications such as strain-insensitive sensing device, multiple-parameter sensors and the distributed sensing measurement along the nonuniform As$_{2}$Se$_{3}$-PMMA tapered fibers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".