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Numerical modelling and experimental validation of pcm-to-air heat exchangers: application of ventilated building envelopes

2019· article· en· W2981451781 on OpenAlexaff
Mohamed Dardir, Mohamed El Mankibi, Fariborz Haghighat

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsConcordia University
Fundersnot available
KeywordsBuilding envelopeEnvironmental scienceHeat exchangerThermal energy storagePhase-change materialLatent heatMeteorologyRadiative transferConvectionThermalASHRAE 90.1Nuclear engineeringThermodynamicsMechanical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract The earlier applications of phase change material (PCM)-to-Air heat exchangers (PAHXs) reported the insufficient cooling charging energy due to system storage abilities, the profile of inlet air temperature, and the charging duration. This paper proposes a developed PAHX system for building envelope applications utilizing both convective and long-wave radiative heat transfer components. A 2D numerical model was proposed utilizing an apparent heat capacity method to represent the PCM latent thermal storage developing both convective and radiative thermal boundaries. The radiative component was developed to study the effect of the system exposure to the night-time sky during the PCM solidification period. The convective component was comprehensively developed mainly between the storage medium (PCM) and the air channel. A real-scale prototype was constructed for the whole model experimental validation. Field experiments were designed and conducted in the warm temperate climate of Lyon, France during summer. The validation criteria were proposed based on ASHRAE guideline 14. The results of the comparison between simulated data and experimentally obtained data showed that the system temperature was within the accepted range of the proposed criteria.

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 score0.034
Threshold uncertainty score0.623

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 head0.027
GPT teacher head0.261
Teacher spread0.235 · 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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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