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Record W1966322262 · doi:10.1109/jqe.2004.828271

Heat dissipation in kilowatt fiber power amplifiers

2004· article· en· W1966322262 on OpenAlexaff
Yong Wang

Bibliographic record

VenueIEEE Journal of Quantum Electronics · 2004
Typearticle
Languageen
FieldEngineering
TopicOptical Network Technologies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDissipationMaterials scienceAmplifierPower (physics)Optical fiberThermal management of electronic devices and systemsDouble-clad fiberFiberOpticsOptoelectronicsDispersion-shifted fiberFiber optic sensorMechanical engineeringEngineeringPhysicsThermodynamics

Abstract

fetched live from OpenAlex

The heat dissipation and output power characteristics of kilowatt ytterbium-doped double-clad (YDDC) fiber power amplifiers are investigated through numerical modeling. Solutions to facilitate heat dissipation and reduce operating temperature in YDDC fibers under bi-directional end pump and distributed pump are presented and compared. It is shown that the heat dissipation issue in kilowatt fiber power amplifiers can be effectively solved by optimizing the arrangement of pump powers, pump absorption coefficients, and fiber lengths.

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)0.001
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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.008
GPT teacher head0.228
Teacher spread0.220 · 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

Citations37
Published2004
Admission routes1
Has abstractyes

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