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Record W3116081071 · doi:10.1016/j.egyr.2020.11.111

Solar optical fiber daylighting system with an IR filter: Experimental and modeling studies

2020· article· en· W3116081071 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

VenueEnergy Reports · 2020
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsUniversité Laval
FundersPrince Mohammad Bin Fahd University
KeywordsMaterials scienceThermoplasticOptical fiberDaylightingSunlightOpticsComposite materialEngineeringArchitectural engineering

Abstract

fetched live from OpenAlex

Solar daylighting system based on low cost thermoplastic optical fiber cables is one of essential and practicable option to save energy associated with electric lighting as well as enhance the visual comfort and human health by using natural solar lighting. In this present study a low-cost solar light system consisting of thermoplastic optical fibers, parabolic mirrored surface and sunlight collector with glass filter to block infrared (IR) radiation, was developed to bring natural sunlight into buildings. The effect of the IR filtration mechanism on the temperature of the thermoplastic optical fiber and the output illuminance, has been examined. The experimental results obviously show that the IR filter would protect the thermoplastic optical fiber from the overheat damage without affecting the output illuminance, which could extend the life time of the thermoplastic polymer optical fiber. Furthermore, an intelligent model based on deep learning neural network (DNN) algorithm was used to predict the temperature at the inlet surface of the thermoplastic optical fiber bundles.

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 score0.087
Threshold uncertainty score0.481

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 head0.021
GPT teacher head0.220
Teacher spread0.200 · 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