MétaCan
Menu
Back to cohort
Record W1929375787

Aparato Experimental Para Avaliação Termo-Energética de Refrigerador Doméstico

2012· article· pt· W1929375787 on OpenAlexaboutno aff
Igor Marcel Gomes Almeida

Bibliographic record

VenueVII CONNEPI - Congresso Norte Nordeste de Pesquisa e Inovação · 2012
Typearticle
Languagept
FieldEngineering
TopicGreen IT and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesPhysicsArt
DOInot available

Abstract

fetched live from OpenAlex

Os esforcos de pesquisa e desenvolvimento na area de Refrigeracao e Climatizacao aplicados ao uso de fluidos refrigerantes naturais nao esta associada somente a necessidade de preservacao do meio-ambiente em si, mas tambem apresenta grande importância na necessidade latente do aumento da eficiencia energetica dos equipamentos. Tal caracteristica e observada na Decisao XIX/6 do Protocolo de Montreal. Neste sentido, identificar fluidos refrigerantes alternativos de longo prazo que satisfacam todos os requisitos com relacao a performance dos sistemas e uma importante area de pesquisa. O objetivo do presente trabalho e analisar as normalizacoes existentes no Brasil, referentes a ensaios em refrigeradores domesticos, e desenvolver a montagem de um aparato experimental para estudo termo-energetico/performance de um refrigerador. Foi desenvolvido um aparato experimental consistindo de um refrigerador domestico de 219 L instrumentado com sensores de pressao, temperatura e corrente eletrica. Os sensores de temperatura e corrente eletrica sao conectados a um sistema de aquisicao de dados para o registro dos dados durante todo o tempo de ensaio. As indicacoes de pressao foram obtidas visualmente atraves de manifold digital. O aparato e adequado para a avaliacao termodinâmica e energetica de um equipamento de refrigeracao operando com fluidos refrigerantes sinteticos ou naturais (hidrocarbonetos), dentro da estrategia de drop-in, sem alteracao dos componentes mecânicos do sistema.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.029
GPT teacher head0.293
Teacher spread0.264 · 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; both teacher heads agree on what is shown here.

Study designObservational
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

Citations0
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueVII CONNEPI - Congresso Norte Nordeste de Pesquisa e InovaçãoSame topicGreen IT and SustainabilityFrench-language works237,207