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Record W1978786335 · doi:10.1115/1.3194764

Thermal Protection of a Ground Layer With Phase Change Materials

2009· article· en· W1978786335 on OpenAlexafffund
Xili Duan, G.F. Naterer

Bibliographic record

VenueJournal of Heat Transfer · 2009
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsOntario Tech UniversityUniversity of Manitoba
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPermafrostMaterials scienceThermalFoundation (evidence)Environmental scienceThermal conductionAmplitudeThermal energy storageThermodynamicsComposite materialGeologyOptics

Abstract

fetched live from OpenAlex

Conventional ground surface insulation can be used to protect power line foundations in permafrost regions from the adverse effects of seasonal freezing and thawing cycles. But previous studies have shown ineffective thermal protection against the receding permafrost with conventional insulation. In this paper, an alternative thermal protection method (phase change materials (PCMs)) is analyzed and studied experimentally. Seasonal ground temperature variations are estimated by an analytical conduction model, with a sinusoidal ground surface temperature variation. A compensation function is introduced to predict temperature variations in the foundation, when the ground surface reaches a certain temperature profile. Measured data are acquired from an experimental test cell to simulate the tower foundation. With thermal energy storage in the PCM layer, the surface temperature of the soil was modified, leading to changes in temperature in the foundation. Measured temperature data show that the PCM thermal barrier effectively reduces the temperature variation amplitude in the foundation, thereby alleviating the seasonal freezing and thawing cycles. Different thermal effects of the PCM thermal barrier were obtained under different air temperature conditions. These are analyzed via melting degree hours and freezing degree hours, compared with a critical number of degree hours.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score0.997

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)0.0040.000

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 head0.081
GPT teacher head0.268
Teacher spread0.187 · 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.

Study designBench or experimental
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

Citations12
Published2009
Admission routes2
Has abstractyes

Explore more

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