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Record W2889802030 · doi:10.1364/ol.43.004679

150  km fast BOTDA based on the optical chirp chain probe wave and Brillouin loss scheme

2018· article· en· W2889802030 on OpenAlexaff
Yongkang Dong, Benzhang Wang, Chao Pang, Dengwang Zhou, Dexin Ba, Hongying Zhang, Xiaoyi Bao

Bibliographic record

VenueOptics Letters · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsUniversity of Ottawa
FundersNatural Science Foundation of Heilongjiang ProvinceNational Natural Science Foundation of China
KeywordsBrillouin zoneBrillouin scatteringChirpOpticsPhysicsSingle-mode optical fiberOptical fiberLaser

Abstract

fetched live from OpenAlex

Distributed long-range Brillouin optical time domain analysis (BOTDA) is an extremely time-consuming sensing scheme, which requires frequency mapping of the Brillouin spectrum and a large number of average times. Here, we propose a fast long-range BOTDA based on the optical chirp chain (OCC) probe wave and Brillouin loss scheme. The OCC-modulated probe wave is enabled by cascading fast-frequency-changing microwave chirp segments head-to-tail, which covers a large frequency range around the anti-Stokes frequency relative to the pump wave. The combination of the OCC technique and Brillouin loss scheme provides several advantages, i.e., fast measurement, a high Brillouin threshold, no additional amplification scheme, and freedom from the nonlocal effect. In the experiment, 6 m spatial resolution, 3.2 s measurement time, and 3 MHz measurement precision were achieved over a 150 km single-mode fiber.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.203
Teacher spread0.192 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations66
Published2018
Admission routes1
Has abstractyes

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