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Numerical study of a PCM-air heat exchanger's thermal performance

2016· article· en· W2534945209 on OpenAlexafffund
Florent Herbinger, Maha Bhouri, Dominic Groulx

Bibliographic record

VenueJournal of Physics Conference Series · 2016
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsHeat transferMechanicsHeat exchangerMaterials scienceMultiphysicsConvective heat transferHVACThermodynamicsLaminar flowThermalPlate fin heat exchangerPlate heat exchangerAir conditioningPhysicsFinite element method

Abstract

fetched live from OpenAlex

In this paper, the use of PCMs in HVAC applications is investigated by studying numerically the thermal performance of a PCM-air heat exchanger. The PCM used in this study is dodecanoic acid. A symmetric 3D model, incorporating conductive and convective heat transfer (air only) as well as laminar flow, was created in COMSOL Multiphysics 5.0. Simulations examined the dependence of the heat transfer rate on the temperature and velocity of the incoming air as well as the size of the channels in the heat exchanger. Results indicated that small channels size lead to a higher heat transfer rates. A similar trend was also obtained for high incoming air temperature, whereas the heat transfer rate was less sensitive to the incoming air velocity.

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 score0.055
Threshold uncertainty score0.374

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 head0.049
GPT teacher head0.274
Teacher spread0.225 · 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

Citations7
Published2016
Admission routes2
Has abstractyes

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