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Record W2767084163 · doi:10.1115/ht2017-4845

Characterization of an Air-PCM Energy Storage Design for Air Handling Unit Applications

2017· article· en· W2767084163 on OpenAlexafffund
Sarah Wert, Cynthia A. Cruickshank, Dominic Groulx

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsDalhousie UniversityCarleton University
FundersPublic Works and Government Services CanadaAkershus UniversitetssykehusGovernment of Canada
KeywordsMaterials scienceThermocoupleThermal energy storageHVACHeat transferEnergy storageAirflowNuclear engineeringStorage tankPhase-change materialEnvironmental scienceMechanical engineeringAir conditioningThermalMeteorologyMechanicsComposite materialEngineeringThermodynamics

Abstract

fetched live from OpenAlex

This paper will discuss the characterization of an air-PCM storage design for commercial air handling unit (AHU) applications during winter. The air-PCM storage design consists of two rows of 29 aluminum flat plate containers (0.45 m × 0.35 m × 0.01 m) filled with PCM, vertically aligned leaving an air channel between each plate of 0.011 m wide. The storage device was placed within a closed air loop which conditions the air to the desired testing temperature and velocity. The PCM selected for testing was RT44HC with a melting temperature of 44 °C. This PCM was chosen for its similar properties to other PCMs having lower melting temperatures (in the range of 5 to 18°C) that could be used in actual HVAC application implementation. The system was instrumented and calibrated with Type T thermocouples and a velocity sensor. The system was tested at various inlet temperatures (55°C to 63°C for charging and 12°C to 25°C for discharging) and flow rates. The instantaneous heat transfer rates and total energy storage were calculated for each test from the data collected. The results provide a baseline value for heat transfer rates in a simple air-PCM design, to be used for model validation.

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: none
Teacher disagreement score0.721
Threshold uncertainty score0.321

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 head0.084
GPT teacher head0.314
Teacher spread0.230 · 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

Citations4
Published2017
Admission routes2
Has abstractyes

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