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Record W3140173155 · doi:10.3390/en14071893

Analysis of Heat Exchange Rate for Low-Depth Modular Ground Heat Exchanger through Real-Scale Experiment

2021· article· en· W3140173155 on OpenAlexaff
Kwonye Kim, Jaemin Kim, Yujin Nam, Euy-Joon Lee, Eun-Chul Kang, Evgueniy Entchev

Bibliographic record

VenueEnergies · 2021
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsNatural Resources Canada
FundersNational Research Foundation of Korea
KeywordsModular designHeat exchangerDrillingHeat pumpPetroleum engineeringEnvironmental scienceNuclear engineeringScale (ratio)Mechanical engineeringEngineeringProcess engineeringMaterials scienceComputer sciencePhysics

Abstract

fetched live from OpenAlex

A ground source heat pump system is a high-performance technology used for maintaining a stable underground temperature all year-round. However, the high costs for installation, such as for boring and drilling, is a drawback that prevents the system to be rapidly introduced into the market. This study proposes a modular ground heat exchanger (GHX) that can compensate for the disadvantages (such as high-boring/drilling costs) of the conventional vertical GHX. Through a real-scale experiment, a modular GHX was manufactured and buried at a depth of 4 m below ground level; the heat exchange rate and the change in underground temperatures during the GHX operation were tracked and calculated. The average heat exchanges rate was 78.98 W/m and 88.83 W/m during heating and cooling periods, respectively; the underground temperature decreased by 1.2 °C during heat extraction and increased by 4.4 °C during heat emission, with the heat pump (HP) working. The study showed that the modular GHX is a cost-effective alternative to the vertical GHX; further research is needed for application to actual small buildings.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.681
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.025
GPT teacher head0.275
Teacher spread0.250 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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