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Record W2091513541 · doi:10.1177/0957650912446902

Use of low grade heat sources in combined ejector–double effect absorption refrigeration systems

2012· article· en· W2091513541 on OpenAlexaff
L. Garousi Farshi, S. S. Mahmoudi, Marc A. Rosen, Mortaza Yari

Bibliographic record

VenueProceedings of the Institution of Mechanical Engineers Part A Journal of Power and Energy · 2012
Typearticle
Languageen
FieldEngineering
TopicRefrigeration and Air Conditioning Technologies
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsRefrigerationCondenser (optics)InjectorLithium bromideThermodynamicsEvaporatorMaterials scienceCrystallizationWaste heatAbsorption (acoustics)Absorption refrigeratorNuclear engineeringProcess engineeringEngineeringComposite materialPhysicsOpticsHeat exchanger

Abstract

fetched live from OpenAlex

At a particular temperature range, heat sources are not hot enough to drive lithium bromide double-effect absorption refrigeration systems efficiently and are too hot to be used for the single effect systems because of the risk of crystallization. To make effective use of heat sources at this temperature range for refrigeration purposes, a combined ejector–double effect absorption cycles are proposed. A computational model is developed to study and compare the effect of operating parameters on the performance of combined and conventional single- and double-effect cycles from the viewpoints of first and second laws of thermodynamics. In addition, because of the importance of crystallization risk in these systems, the effect of varying working conditions on the possibility of crystallization is investigated too. The results show the advantageous performance of the combined cycle compared to that of the single- and double-effect systems at particular ranges of heat source temperature. These temperature ranges are extended at lower evaporator and higher condenser or absorber temperatures.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.296
Threshold uncertainty score0.339

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 communication0.0000.001
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 head0.013
GPT teacher head0.204
Teacher spread0.191 · 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

Citations20
Published2012
Admission routes1
Has abstractyes

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Same venueProceedings of the Institution of Mechanical Engineers Part A Journal of Power and EnergySame topicRefrigeration and Air Conditioning TechnologiesFrench-language works237,207