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Record W2912091791 · doi:10.1139/cjp-2018-0878

Gas radiative effects on gas-filled flat plate solar collectors

2019· article· en· W2912091791 on OpenAlexaffvenue
Khosro Lari, Ali Tarokh, Mohammad Naghizadeh

Bibliographic record

VenueCanadian Journal of Physics · 2019
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsLakehead University
Fundersnot available
KeywordsRadiative transferPhysicsThermalAbsorption (acoustics)Nanofluids in solar collectorsHeat transferMechanicsConvectionOpticsPhotovoltaic thermal hybrid solar collectorThermodynamicsMeteorologyComputational physics

Abstract

fetched live from OpenAlex

A standard thermal solar collector can be used for both hot water production and air heating purposes. Gas-filled solar collectors represent a new emerging design approach with enhanced characteristics. In this research, numerical modeling is utilized to study radiative effects of the participating gases on the performance of solar collectors. The coupled radiative–convective heat transfer in the solar collector is considered and the collector cavity is considered as a radiatively participating medium. The finite volume method has been adopted to solve the governing equations and discrete ordinates method is used for radiative transfer. After validating the model used in this study, it is used to obtain the heat transfer characteristics of a flat-plate solar collector with real solar conditions of the city of Kerman, Iran, in summer at a wide range of air absorption coefficients. According to the results, by increasing the absorption coefficient of the air, the temperature of the absorber plate is reduced and the air temperature is increased, but the increase of air temperature is much higher than the reduction of absorber temperature. Hence, it is concluded that it is possible to use participating gases in the solar air heaters to enhance the performance of the collector.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.788

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 head0.006
GPT teacher head0.177
Teacher spread0.171 · 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.

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

Citations1
Published2019
Admission routes2
Has abstractyes

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