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Record W3178069164 · doi:10.3390/pr9071160

Storing Energy from External Power Supplies Using Phase Change Materials and Various Pipe Configurations

2021· article· en· W3178069164 on OpenAlexaff
Daniel Aprile, Samer Al-Banna, Arraventhan Maheswaran, Joshua Paquette, M. Ziad Saghir

Bibliographic record

VenueProcesses · 2021
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsToronto Metropolitan University
FundersQatar National Research FundQatar Foundation
KeywordsNusselt numberHeat transferMaterials scienceMicro-loop heat pipePhase-change materialMechanicsHeat transfer enhancementPipe flowFriction lossHeat pipeInsert (composites)Reynolds numberHeat transfer coefficientThermodynamicsComposite materialTurbulencePhase changePhysics

Abstract

fetched live from OpenAlex

Phase change materials are commonly used for energy storage. Heat transfer enhancement and heat storage are the two main goals in this paper. A cylindrical pipe covered with phase change material is investigated numerically. Ideally, a high temperature liquid flows through the pipe, resulting in heat transferred to the phase change material. To enhance the heat transfer, various configurations involving the addition of a twisted tape inside of the pipe and the use of helical shape pipes were investigated. A straight pipe with no twisted tape insert was also analyzed and used as a benchmark case. All the configurations had constant properties such as material selection, overall size, pipe diameter and inlet Reynold’s number, so the performance could be compared under similar conditions. All initial configurations were simulated and the heat transfer rate, Nusselt number, friction factor and performance evaluation criterion (PEC) of the designs were determined. It was found that the heat transfer rate and Nusselt number of all the various designs yielded higher results than the reference straight pipe configuration. Additionally, due to the added complexity in the flow caused by the insert, the friction factor of all the configurations was also higher. The helical pipe configuration was the only configuration that had a PEC higher than that of the reference straight pipe. This is because the negative impacts caused by the friction factor outweighed the gains in Nusselt number for the twisted tape designs. It was also hypothesized that lowering the inner diameter of the helical pipe would increase the PEC. Further simulations with modified inner diameters were done to test the hypothesis. The simulations confirmed the hypothesis, as the pipes with inner diameters 0.75 and 0.5 cm led to a 50% and 150% increase in the PEC respectively, when compared to an inner diameter of 1 cm. It was also determined that smaller inner diameters led to lower outlet temperatures meaning a higher percentage of the thermal energy from the fluid was transferred to the phase change material.

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 categoriesInsufficient payload (model declined to judge)
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 score0.016
Threshold uncertainty score1.000

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)0.0010.000

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 head0.068
GPT teacher head0.310
Teacher spread0.243 · 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.

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

Citations2
Published2021
Admission routes1
Has abstractyes

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