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Record W4283592424 · doi:10.11159/ehst22.138

Investigating Phase Change Material Foam Configuration in a Heat Exchanger

2022· article· en· W4283592424 on OpenAlexafffund
Kasra Ghasemi, Mohammad Reza Mohaghegh, Mehran Bozorgi, Syeda Humaira Tasnim, Shohel Mahmud

Bibliographic record

VenueProceedings of the International Conference of Energy Harvesting, Storage, and Transfer · 2022
Typearticle
Languageen
FieldEngineering
TopicAdditive Manufacturing and 3D Printing Technologies
Canadian institutionsUniversity of Guelph
FundersMinistry of Agriculture, Food and Rural AffairsOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsHeat exchangerPhase-change materialMaterials sciencePhase changePhase (matter)Composite materialMechanical engineeringChemistryEngineeringEngineering physics

Abstract

fetched live from OpenAlex

Phase change material can be used in a heat exchanger to smooth out the temperature during cyclic or pulsed operations. However, the performance is highly dependent on the design and thermophysical properties of embedded PCM. In this study, the effects of location and amount of embedded PCM on the melting time in a shell and tube heat exchanger are evaluated by developing a Lattice Boltzmann Method code. The PCM is encapsulated in circular metal foam surrounding the inner tube using hot water as the working fluid. According to the results, inner tube location has a significant effect on the natural convection, and consequently, the melting time and rate. It is observed that placing the inner tube near to the downside of the PCM layer, causes a more uniform temperature distribution within the domain and has the lowest melting time. Also, while increasing the thickness of the PCM layer enhances the melting time, this increment has an exponential relation with the melting time.

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 score0.156
Threshold uncertainty score0.465

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 head0.043
GPT teacher head0.237
Teacher spread0.194 · 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

Citations3
Published2022
Admission routes2
Has abstractyes

Explore more

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