MétaCan
Menu
Back to cohort
Record W2556062261 · doi:10.1115/ht2016-7232

Effect of Heat Source Geometry on the Transient Heat Transfer During Melting Process of a PCM

2016· article· en· W2556062261 on OpenAlexafffund
Mohammad Khairul Bashar, Kamran Siddiqui

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHeat transferMaterials scienceHeat transfer coefficientConvective heat transferThermodynamicsPhase-change materialConvectionVolume (thermodynamics)MechanicsThermalPhysics

Abstract

fetched live from OpenAlex

Thermal energy storage (TES) systems using phase change materials (PCMs) are used in various engineering applications. TES is a means by which heat is ‘hold’ for a certain period of time for use at a later time. We report an experimental study which was conducted to investigate the melting process and associated heat transfer in a rectangular chamber with a cylindrical u-shaped heat source imbedded inside the PCM. The results showed that geometry and orientation of the heat source immensely influenced the heat transfer behavior during solid-liquid phase transition. The heat transfer behavior, interface movement and the heat transfer coefficients differed both axially and vertically inside the chamber as well as with the melting rate. The local convective heat transfer coefficient, hlocal in the inner region, enclosed by the U-tube, was observed to increase at a higher rate than the outer region. Stronger convective flow and a lower viscosity owing to higher temperature in the inner region is believed to have caused faster melting in this region. The melting rate was also found comparatively higher until approximately two-third of the PCM volume was melted before the rate declined.

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)0.001
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 score0.004
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.014
GPT teacher head0.260
Teacher spread0.246 · 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
Published2016
Admission routes2
Has abstractyes

Explore more

Same topicPhase Change Materials ResearchFrench-language works237,207