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Record W1997674002 · doi:10.1364/oe.22.00a248

GRIN planar waveguide concentrator used with a single axis tracker

2014· article· en· W1997674002 on OpenAlexafffund
Sébastien Bouchard, Simon Thibault

Bibliographic record

VenueOptics Express · 2014
Typearticle
Languageen
FieldEngineering
Topicsolar cell performance optimization
Canadian institutionsInstitut National d'Optique
FundersNatural Sciences and Engineering Research Council of CanadaSynopsys
KeywordsConcentratorOpticsNonimaging opticsPlanarWaveguideMaterials scienceSolar trackerFresnel lensFresnel equationsBlock (permutation group theory)Refractive indexSolar energyPhotovoltaic systemComputer sciencePhysicsElectrical engineeringLens (geology)Engineering

Abstract

fetched live from OpenAlex

It is generally accepted that small to medium level concentrators could be used as cost-competitive replacements for tracked solar panels. The objective is to design a system that can reach a good level of sun concentration with only one sun-tracking axis and is cheap to fabricate. As the most critical parameter for all concentrator designs, optical efficiency needed improvement to reduce the cost of power produced by our system. By using a graded-index planar waveguide with an index profile similar to SELFOC fiber, the ray's path can be controlled. Also, the concentrator can be fabricated in a single block, which reduces Fresnel reflections. Overall, the optical efficiency can be improved by as much as 33% compared to the same system made with a homogeneous waveguide. Furthermore, the ability to cost-effectively fabricate the concentrator by molding can be preserved, making it possible to reduce the cost of the solar power produced.

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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.010
GPT teacher head0.186
Teacher spread0.176 · 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

Citations19
Published2014
Admission routes2
Has abstractyes

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