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Record W4389584911 · doi:10.17118/11143/21006

On the thermal performance of spiral-coil energy piles in a coldclimate

2023· article· en· W4389584911 on OpenAlexaff
Reyhaneh Nazmabadi, Ali Hakaki-Fard

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicIntegrated Energy Systems Optimization
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsElectromagnetic coilSpiral (railway)ThermalCold climateMaterials scienceElectrical engineeringMechanical engineeringEngineeringPhysicsMeteorology

Abstract

fetched live from OpenAlex

Abstract: Energy piles have been developed as Ground Heat Exchangers (GHEs) in Ground Source Heat Pump (GSHP) systems to enhance the thermal performance of Heating, Ventilation, and Air Conditioning (HVAC) systems for buildings. The idea of the energy pile stems from the fact that the ground temperature in depths more than 8–15m is nearly constant throughout the year. This study investigates the thermal performance of a GSHP combined with spiral-coil energy piles for space heating of a residential building in a cold climate. A three-dimensional transient Computational Fluid Dynamics (CFD) model of the spiral-coil energy pile coupled to the GSHP and the surrounding soil is developed. This model is then used to investigate the effect of design parameters, including GHE diameter and GHE pitch, on the thermal performance of the studied GSHP. Then, a five-year operation of the system is simulated. It is concluded that the increase in GHE diameter and GHE pitch enhances the thermal performance of the system. Moreover, the performance of the studied GSHP in a cold climate gradually declines in a long-term operation due to the cold accumulation in the pile and surrounding ground.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.071
Threshold uncertainty score0.203

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 head0.008
GPT teacher head0.175
Teacher spread0.167 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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