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Long-term performance investigation of a GSHP with actual size energy pile with PCM

2022· article· en· W4220769788 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueApplied Thermal Engineering · 2022
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsHeat pumpPileBoreholePhase-change materialGeothermal energyFoundation (evidence)EngineeringHeat exchangerCoefficient of performanceThermal energy storageGeothermal gradientGeotechnical engineeringMaterials sciencePhase changeMechanical engineeringGeologyThermodynamics

Abstract

fetched live from OpenAlex

The use of geothermal energy has increased significantly (90 time) since 1995. Among these increases, Ground Source Heat Pumps (GSHP) has contributed by 40 times in an effort to reduce the burning of fossil fuels and contribute to the reduction of green house gas emissions. The space requirements and high initial cost of borehole fields hinder the widespread use of GSHPs. The use of foundation piles, used as a ground heat exchanger, has been proposed to overcome these limitations. Research has shown that foundation piles have a lower depth and smaller spacing compared to boreholes. Phase Change Materials (PCMs) have been proposed as a potential solution to increase the storage capacity and decrease the thermal radius of energy piles. In the current study, a 3-D finite element model was developed to study the effects of PCMs on the performance of energy piles against a real building load for a complete year, while integrating an actual heat pump (HP) performance curve into the numerical model. The effects of the PCM location and melting range were also investigated. The study revealed a 5.2% enhancement in the Coefficient of Performance (COP) during the melting of the PCM, and a negative effect of up to 1.8% during the completely solid-state. Locating the PCM cylinders inside of the concrete shell led to better performance compared to when the PCM cylinders were located outside of the concrete shell. The best locations were found to be between the center of he pile and the U-loop. The PCM melting range of (4–6)°C was better than the melting range of (1–3)°C for the current study load. Lastly, the use of multiple PCM melting temperatures for a given design was investigated. The results revealed that the use of multiple PCM melting temperatures led to a performance enhancement of up to 26%.

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.

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 score0.717
Threshold uncertainty score0.731

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 head0.005
GPT teacher head0.157
Teacher spread0.151 · 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