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Record W2967400245 · doi:10.1061/9780784482599.053

Thermal Performance of a Proposed Geothermal Piles System for Re-Harvesting Heat Loss through the Building Below-Grade Enclosure in Cold Regions

2019· article· en· W2967400245 on OpenAlexaffabout
Maryam Saaly, Pooneh Maghoul

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsGeothermal gradientGeothermal heatingEnvironmental scienceAtticEnclosureBuilding envelopeThermal energy storagePileGeothermal energyThermalGeotechnical engineeringGeologyCivil engineeringEngineeringMeteorologyGeography

Abstract

fetched live from OpenAlex

Thermal performance of a proposed group of geothermal piles for supplying the energy demand of a building is studied in this paper. The building is located in the Fort-Garry campus of the University of Manitoba in Winnipeg, MB, Canada. Due to the heat loss of the below-grade envelope of buildings in urban areas, soil temperature rises significantly. The proposed geothermal piles are aimed at re-harvesting the heat leaked into the ground through the basement structure. Further, the thermal performance of the proposed geothermal pile system has been analyzed numerically. One of the most important impediments for wide application of geothermal piles in cold regions like Canada, where annual heat extraction from the soil is higher than heat rejection into it, is the underground thermal imbalance which is widely investigated in this study. Based on the results, the temperature of the soil increases up to 6°C due to the heat leakage of basements of both studied building and its surrounding buildings. Despite the injected heat to the ground due to the building heat leakage, the thermal imbalance occurs in the soil in case of supplying 100% of the building heat demand during the winter and 100% of its cold demand during the summer by geothermal piles which necessitates further consideration for efficient application of geothermal energy using thermal piles in Canada.

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 score0.467
Threshold uncertainty score0.992

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 head0.019
GPT teacher head0.237
Teacher spread0.219 · 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
Published2019
Admission routes2
Has abstractyes

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