A generalized thermal conductivity model for soils and construction materials
Bibliographic record
Abstract
This paper intends to develop a generalized thermal conductivity model for moist soils that is based on the concept of normalized thermal conductivity with respect to dry and saturated states. This model integrates well the effects of porosity, degree of saturation, mineral content, grain-size distribution, and particle shape on the thermal conductivity of unfrozen and frozen soils. The thermal conductivity for saturated soils is computed with the use of a well-known geometric model that includes the unfrozen water content in frozen fine-grained soils. Nearly 220 experimental results available from the literature were analysed to develop a generalized empirical relationship to assess the thermal conductivity of dry soils. A general relationship between the normalized thermal conductivity of soils and the degree of saturation using a soil-type dependent factor was used to correlate the normalized thermal conductivity for more than 650 test results for unfrozen and frozen moist soils, such as gravels, sands, silts, clays, peat, and crushed rocks.Key words: heat transfer, soils, degree of saturation, mineral content, unfrozenfrozen, thermal conductivity.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".