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Record W2143459174 · doi:10.5539/mas.v6n1p136

Designing, Construction and Analysis of Speed Control System of the Fan with PV Feeding Source in an Air Solar Collector

2011· article· en· W2143459174 on OpenAlexvenueno aff
Amir Hematian, Yahya Ajabshehichi, Hossein Behfar, Hessamoddin Ghahramani

Bibliographic record

VenueModern Applied Science · 2011
Typearticle
Languageen
FieldEnergy
TopicSolar Thermal and Photovoltaic Systems
Canadian institutionsnot available
Fundersnot available
KeywordsPhotovoltaic systemEnvironmental scienceSolar energyRenewable energyAutomotive engineeringMicrocontrollerElectrical engineeringMeteorologyComputer scienceEngineeringPhysics

Abstract

fetched live from OpenAlex

Solar energy is one of the renewable energy sources which can be received more by designing more accurate systems. In this article a flat solar collector with the area of 2×1m2 and thickness of 0.5mm, made of steel iron in the form of venetian blinds (in order to increase exposure to air) has been used. The surface of absorber plate was black and for insulation of the body of the collector glass wool has been used with 5 cm thickness. One of the essential problems of air solar collectors is that the temperature of the exiting air temperature from the collector is variable during the day and their efficiency is low in the last hours of the day and also when the weather suddenly gets cloudy .In this study, to keep constant the exiting air from the collector consistent in the desired limits, a control system is designed and constructed by applying photovoltaic cells, a microcontroller (AVR) and temperature sensors (LM35). Three temperature sensors were installed in the exit of the collector .The experiment results showed that by automatic change of the fan's speed in the designed system, the exiting temperature of the collector was obtained in the desired limits which is an outstanding advantage for various applications.

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)0.001
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 score0.446
Threshold uncertainty score0.367

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.017
GPT teacher head0.197
Teacher spread0.179 · 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

Citations9
Published2011
Admission routes1
Has abstractyes

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