MétaCan
Menu
Back to cohort
Record W7014567307

PERFORMANCE OF HEAT PUMP CHILLED FOUNDATIONS

2015· article· en· W7014567307 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2015
Typearticle
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsHeat pumpAir source heat pumpsThermal energy storageHeat recovery ventilationPermafrostThermal
DOInot available

Abstract

fetched live from OpenAlex

Standard domestic ground coupled heat pump technology has been applied to maintain frozen ground in and beneath insulated slab-on-grade foundations while simultaneously providing substantial heat for the building itself. Thermal and economic performance data are presented for the first year of operation of two-350 m2 multi-purpose municipal garage buildings located on permafrost in the W o n. The two cases bracket the range of soil conditions, ground temperatures, operating conditions and logistic problems likely to be encountered in practice. The thermal regime within the foundations was simulated by a numerical model.and the results were used to suggest ways of improving the design. The ground coupled heat pump chilled foundation has the advantage, relative to the alternatives, of beiig less affected by external air temperatures. Initial construction is cheap while net operating costs for electic heat pumps range from negligible to reasonably acceptable. Diesel or natural gas driven heat pumps would further reduce operating costs. The paper also suggests additional possible applications of groundcoupled heat pumps to permafrost engineering. On a utilis6 la technologic d6jB mike des thermopompes domestiques dans le contexte des fondations du type dalle-sur-sol pour conserver le pergdliiol sous-jawnt dam un &at gel6 tout en produisant une quantiti? importante de chaleur pour le chauffage du bftiment lui-msme. On pr6sente des donnkes de performance thermique et Bconornique pour la prem&e annde d'ophation de deux bitiments municipaux polyvalents de

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.752
Threshold uncertainty score0.463

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 head0.024
GPT teacher head0.244
Teacher spread0.220 · 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 designNot applicable
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
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueNPARCSame topicGeothermal Energy Systems and ApplicationsFrench-language works237,207