Influence of stress history on thermal conductivity of saturated fine-grained soils
Bibliographic record
Abstract
This research investigated variations in thermal conductivity k for normally consolidated (NC) and overconsolidated (OC) saturated fine-grained soils at different levels of vertical effective stress. A series of undrained heating tests were performed using a specially designed consolidometer with central radial heating arrangement and temperature measurements within a soil specimen. For different soils investigated in this research, k correlated well with soil consolidation characteristics (compression index λ and swelling index κ) and vertical effective stress σvʹ at both NC and OC states. However, the rates of increment of steady- and transient-state values of k ( kst and ktr, respectively) with σv′ differed from one soil to another. For OC clays, both ktr and kst increased with preconsolidation stress σc′. A set of equations were proposed to estimate both kst and ktr for saturated fine-grained soils as functions of σv′, λ, κ, and stress history. At a particular value of σvʹ, the dependence of k on overconsolidation ratio (OCR) and σc′ marked the importance of considering stress history in the determination of k. The influence of soil mineral composition on k was also explored. Quantification of soil mineralogical composition and available data on mineral thermal conductivity enabled prediction of ktr with reasonable accuracy.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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".