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Record W2775043845 · doi:10.1002/ente.201700417

Numerical Study on the Combined Heat and Mass Recovery Adsorption Cooling Cycle

2017· article· en· W2775043845 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueEnergy Technology · 2017
Typearticle
Languageen
FieldEngineering
TopicAdsorption and Cooling Systems
Canadian institutionsNexen (Canada)
FundersNational Research Foundation of Korea
KeywordsCoefficient of performanceHeat recovery ventilationThermodynamicsMaterials scienceAdsorptionChemistryHeat pumpHeat exchangerPhysics

Abstract

fetched live from OpenAlex

Abstract A numerical simulation of the performance of a fin‐tube‐type adsorption bed with silica gel/water working pairs was conducted. Three models of the heat recovery cycle, the mass recovery cycle, and a combined heat and mass recovery cycle were closely examined. The main goals were to determine 1) the conditions under which these advanced cycles were most effective and 2) the optimum recovery time. Mass recovery enhanced both the coefficient of performance (COP) and specific cooling power (SCP) by up to 24 and 37.5 %, respectively, at 60 °C, and the enhancements of the COP and SCP were 5.0 and 16.0 %, respectively, at 90 °C. Heat recovery increased the COP by 12.56 %, but reduced the SCP by 10.84 % at 60 °C, whereas, at 90 °C, the COP increased by 11.83 % and SCP decreased by 5.96 %. The mass recovery is more influential at a low heating temperature than that at a high heating temperature. Therefore, in the combined heat and mass recovery cycles, the main contribution to the enhancement of the COP comes from mass recovery at lower water temperature. However, at a high heating temperature, the COP increases mainly due to heat recovery.

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.

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 score0.572
Threshold uncertainty score0.380

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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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