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Record W3210161069 · doi:10.32920/ryerson.14663220.v1

Experimental And Numerical Invetigation Of Dependence Of Soil Thermal Conductivity On Temperature Water Content, And Soil Texture

2021· preprint· en· W3210161069 on OpenAlexaff
Behnam Jowkar-Baniani

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEnergy
TopicGeothermal Energy Systems and Applications
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsLoamSoil textureThermal conductivitySaturation (graph theory)Soil scienceWater contentTexture (cosmology)Soil thermal propertiesMaterials scienceHydraulic conductivityEnvironmental scienceSoil waterGeotechnical engineeringGeologyComposite materialMathematics

Abstract

fetched live from OpenAlex

Comprehensive set of thermal conductivity data for a loam soil was generated, for temperature variations from 5ºC to 92ºC and water content variations from dry to saturation, and compared to two other soil textures. The results exhibited similar characteristics as those of the other textures, where a significant change in soil thermal conductivity was. Using the thermal conductivity data sets, a model representing heat and mass transfer in soil was used to study the apparent thermal conductivity due to vapour migration. In addition, a computer simulation of a ground source heat pump system was developed, where the experimental data was used to investigate the impact of water content and soil texture variation on the GSHP performance. It was observed that the GSHP energy consumption varied more prominently when the soil wetness varied from dryness to full saturation and less significantly when the soil type varied from coarse to finer texture.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.993

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 head0.028
GPT teacher head0.245
Teacher spread0.218 · 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 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

Citations0
Published2021
Admission routes1
Has abstractyes

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