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Record W4319782148 · doi:10.1115/imece2022-95940

Design, Construction, and Thermodynamic Analysis of a Direct-Expansion Solar Assisted Heat Pump for Cold Climates

2022· article· en· W4319782148 on OpenAlexaffabout
Nadia Elgamal, Jessica Sambi, Dhruvi Patel, Charuka Marasinghe, Edwin Pulikkottil, Kerwin Virtusio, Aggrey Mwesigye, Simon Li

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsHeat pumpSolar energyNuclear engineeringMechanical engineeringEnvironmental scienceThermodynamicsEngineeringHeat exchangerPhysicsElectrical engineering

Abstract

fetched live from OpenAlex

Abstract Direct expansion solar assisted heat pump (DX-SAHP) systems have the potential to provide the heat load required for domestic hot water (DHW) sustainably and with minimum emissions. DX-SAHPs utilize a solar thermal collector to evaporate a working fluid. By using less energy in the process, these systems can achieve higher coefficients of performance (COP) than those afforded by conventional air source heat pumps. With Calgary possessing the highest solar potential in Canada of about 2396 hours of sunlight available 333 days a year [1], the implementation of such systems would make technical and economic sense. In this paper, the design, fabrication, and testing of a DX-SAHP system for cold climates is presented. A mathematical model representing the system was developed by combining the Hottel-Whillier-Bliss equation for the solar collector and a control volume analysis using the first law of thermodynamics for the heat pump cycle. Theoretical results demonstrate that a COP in the range of 3.4–4.5 is achievable. With the promising theoretical results, an experimental test setup was designed, constructed, and instrumented to determine the long-term performance of a DX-SAHP under local climatic conditions.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.560
Threshold uncertainty score0.753

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.231
Teacher spread0.216 · 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 designSimulation or modeling
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

Citations1
Published2022
Admission routes2
Has abstractyes

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