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Record W2978136476 · doi:10.7567/1347-4065/ab4a93

Monte Carlo simulation of a transversely excited solar-pumped fiber laser

2019· article· en· W2978136476 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJapanese Journal of Applied Physics · 2019
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsOpticsMonte Carlo methodDichroic glassReflector (photography)Materials scienceLaserFiberAbsorption (acoustics)Aperture (computer memory)Distributed ray tracingNumerical aperturePhotonRadiationSolar simulatorRay tracing (physics)OptoelectronicsPhysicsSolar cell

Abstract

fetched live from OpenAlex

Abstract A Monte Carlo ray-tracing simulation was developed for a transversely excited solar-pumped fiber laser without focusing optics. To make this possible, the fiber is immersed in a liquid sensitizer and sandwiched between highly reflective mirrors. The top reflector is dichroic to transmit solar radiation but reflect fluorescence to confine photons that match the absorption band of the active fiber. Simulation was used to evaluate the validity of the concept and optimize device performance. For comparison with the calculations, preliminary experiments were conducted by illuminating a 30 cm aperture, laser module with a solar simulator. The observed gains were in good agreement with the calculations for various conditions, such as sensitizer concentration and mirror reflectivity. Finally, we show that the predicted output power reaches 29 mW when the fiber length is optimized, and it will be enhanced to 150 mW with 0.21% solar-to-laser efficiency under the assumption of a reabsorption-free sensitizer.

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.

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 categoriesnone
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 score0.020
Threshold uncertainty score0.482

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 head0.007
GPT teacher head0.195
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