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Record W3036570846 · doi:10.3390/cleantechnol2020014

Critical Review on Efficiency of Ground Heat Exchangers in Heat Pump Systems

2020· article· en· W3036570846 on OpenAlexafffund
Adel Eswiasi, Phalguni Mukhopadhyaya

Bibliographic record

VenueClean Technologies · 2020
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of Victoria
FundersMinistry of Higher Education and Scientific ResearchCanadian Bureau for International Education
KeywordsHeat pumpHeat pipeBoreholeHeat exchangerHeat transferEnvironmental sciencePlate heat exchangerGroutThermal energy storageThermalCopper in heat exchangersAir source heat pumpsNuclear engineeringMaterials sciencePlate fin heat exchangerMechanical engineeringMechanicsGeotechnical engineeringEngineeringThermodynamicsComposite material

Abstract

fetched live from OpenAlex

Use of ground source heat pumps has increased significantly in recent years for space heating and cooling of residential houses and commercial buildings, in both heating (i.e., cold region) and cooling (i.e., warm region) dominated climates, due to its low carbon footprint. Ground source heat pumps exploit the passive energy storage capacity of the ground for heating and cooling of buildings. The main focus of this paper is to critically review how different construction and operation parameters (e.g., pipe configuration, pipe diameter, grout, heat injection rate, and volumetric flow rate) have an impact on the thermal efficiency of the vertical ground heat exchanger (VGHE) in a ground source heat pump (GSHP) system. The published literatures indicate that thermal performance of VGHEs increases with an increase of borehole diameter and/or pipe diameter. These literatures show that the borehole thermal resistance of VGHEs decreases within a range of 9% to 52% due to pipe configurations and grout materials. Furthermore, this paper also identifies the scope to increase the thermal efficiency of VGHE. The authors conclude that in order to enhance the heat transfer rate in VGHE, any attempt to increase the surface area of the pipe configuration would likely be an effective solution.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.003

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 head0.041
GPT teacher head0.271
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations32
Published2020
Admission routes2
Has abstractyes

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