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Record W3137615454 · doi:10.1364/ao.419837

Distributed strain and temperature sensing over 100  km using tunable-wavelength OTDR based on MEMS filters

2021· article· en· W3137615454 on OpenAlexaff
M. A. Taranov, B. G. Gorshkov, А. Э. Алексеев, В. Т. Потапов

Bibliographic record

VenueApplied Optics · 2021
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsOptical time-domain reflectometerMaterials scienceOpticsRaman amplificationNarrowbandFiber optic sensorMicroelectromechanical systemsOptical fiberFiber Bragg gratingOptoelectronicsWavelength-division multiplexingWavelengthTemperature measurementRaman spectroscopyPolarization-maintaining optical fiberRaman scatteringPhysics

Abstract

fetched live from OpenAlex

The possibility of distributed wide-range strain and temperature measurements in a 100 km long optical fiber using tunable-wavelength low-coherence optical time-domain reflectometer (OTDR) is demonstrated. The specified distance range is provided by employing two narrowband microelectromechanical system (MEMS) spectral filters tuned synchronously as well as by taking advantage of Raman amplification and amplification by remotely pumped erbium-doped fiber segments built into the fiber under test. With the time of a single measurement of 10 min and the spatial resolution of about 1 m, the measurement range reached 1000 µɛ in strain units, which is equivalent to the temperature range of 110°C.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.218
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 head0.012
GPT teacher head0.218
Teacher spread0.206 · 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 designSimulation or modeling
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

Citations7
Published2021
Admission routes1
Has abstractyes

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