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Record W7036564510

Carbon Dioxide Medium Temperature Refrigeration System With Thermal Storage

2021· article· en· W7036564510 on OpenAlexaboutno aff

Bibliographic record

VenuePurdue e-Pubs (Purdue University System) · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMediterranean and Iberian flora and fauna
Canadian institutionsnot available
Fundersnot available
KeywordsRefrigerationThermal energy storageTranscritical cycleRefrigerantVapor-compression refrigerationEvaporatorEnergy consumptionCooling capacityThermal
DOInot available

Abstract

fetched live from OpenAlex

Application of Carbon Dioxide as a natural, non-toxic, non-flammable refrigerant in refrigeration systems is steadily gaining interest, especially in locations with moderate climate, like Europe or Canada. However, it is a well-known fact that at higher ambient conditions, when CO2 system operates in transcritical mode, system efficiency is substantially reduced. Currently, there is a large variety of different techniques aimed at the CO2 refrigeration system efficiency enhancement at transcritical operation, like vapor injection, ejectors, expanders, multi-stage compression with intercooling (and combinations thereof) to name a few. On the other hand, thermal storage devices are gaining popularity in many applications including supermarkets, As an alternative approach to other CO2 system enhancement, a novel MT refrigeration CO2 system with a closed couples thermal storage battery is introduced and evaluated. Thermal storage system has a phase change temperature higher than the evaporator temperature and facilitates heat exchange between CO2 and Phase change material. Its operation is simple to be controlled and has, within limitations, very high roundtrip efficiency. The current paper provides the description of this system, explains its modes of operation, reviews experimental investigation of the system with a scaled down thermal storage device. Performance of this system is evaluated using analysis model at different modes of operation. Scaled for a typical 4TON MT REF system, its monthly energy and energy cost consumption is evaluated and compared with a similar sized ejector-enhanced CO2 system, having typical weather and load profile, while applying different energy cost models. Performance of this system is evaluated using analysis model at different modes of operation. Scaled for a typical 4TON MT REF system, its monthly energy and energy cost consumption is evaluated and compared with a similar sized ejector-enhanced CO2 system, having typical weather and load profile, while applying different energy cost models.

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 score0.845
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.007
GPT teacher head0.148
Teacher spread0.141 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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