MétaCan
Menu
Back to cohort

Development of a high efficient NH3/CO2 refrigeration system.

2019· article· en· W3015619910 on OpenAlexaboutno aff
Kazuhiro Hattori, R. Arimoto, I Terashima

Bibliographic record

VenueInstitut International du Froid · 2019
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerantRefrigerationMontreal ProtocolEnvironmental scienceOzone layerProcess engineeringWork (physics)Waste managementGlobal warmingComputer scienceEngineeringOzoneMeteorologyGas compressorClimate changeMechanical engineeringGeographyEcology

Abstract

fetched live from OpenAlex

Environmental problems such as ozone layer depletion and global warming are widely known as global issues. The Montreal Protocol totally prohibits use of HCFC from 2020 and Kigali revision of the protocol calls for gradual reduction of use of HFC by 85% towards 2036. In the industrial refrigeration, HCFC-22 refrigerant has been used for many years and HFC refrigerants are widely used as alternatives, however, conversion to refrigerants with less environmental impact is urgently required. Mayekawa developed and introduced a highly efficient refrigeration system called ‘NewTon’, applying the natural refrigerants ammonia (NH3) and carbon dioxide (CO2) as the primary and secondary refrigerants. The refrigeration system demonstrates a high energy saving compared to systems with traditional working fluids and in addition its direct environmental impact can be neglected since only natural working fluids are applied. These kind of units are widely used in freezing- and cold storage applications. In this work, the specific features of the ‘NewTon’ unit are described and energy consumptions are compared with historical demands of the systems, which have been replaced.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.386
Threshold uncertainty score0.470

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 head0.190
Teacher spread0.185 · 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 designSimulation or modeling
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
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInstitut International du FroidSame topicRefrigeration and Air Conditioning TechnologiesFrench-language works237,207