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Record W1970164664 · doi:10.1117/12.657643

Combined Raman and Brillouin scattering sensor for simultaneous high-resolution measurement of temperature and strain

2006· article· en· W1970164664 on OpenAlexafffund
Kellie Brown, Anthony W. Brown, Bruce G. Colpitts

Bibliographic record

VenueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 2006
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsUniversity of New Brunswick
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBrillouin scatteringBrillouin zoneMaterials scienceRaman scatteringTemperature measurementRaman spectroscopyStrain (injury)Image resolutionOpticsOptical fiberFiber optic sensorDistributed acoustic sensingResolution (logic)ScatteringOptoelectronicsPhysicsComputer science

Abstract

fetched live from OpenAlex

Recently, strain and temperature measurement results using the first ever spontaneous Brillouin and Raman scattering based fiber optic sensor have been reported (Alahbabi et al., 2004)<sup>1</sup>. This contribution reports the performance results of a combined Brillouin and Raman sensor used to measure strain and temperature simultaneously. We report on a sensor based on the combination of a BOTDA loss-based Brillouin sensor and a spontaneous Raman scattering based sensor, which has not been previously reported to date. We have implemented the combined sensor system for operation over useful sensing lengths and show significantly improved temperature and strain accuracy along with superior spatial resolution. This combined sensor system is shown to be capable of separating temperature and strain effects which previously limited Brillouin systems in some applications.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.597
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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 communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.008
GPT teacher head0.196
Teacher spread0.188 · 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 teacher head, not a consensus.

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

Citations4
Published2006
Admission routes2
Has abstractyes

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Same venueProceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIESame topicOptical Network TechnologiesFrench-language works237,207