Comparison of Laboratory Methods for Measuring Thermal Conductivity of Unsaturated Soils
Bibliographic record
Abstract
Experiments were conducted to explore three different laboratory approaches for determining the relationship between thermal conductivity (λ) and saturation (S) ("thermal dryout curves") for unsaturated coarse-grained porous media. These include: (i) a single-sample approach involving evaporation from a sample with an embedded thermal conductivity probe; (ii) a multiple-sample approach involving subsamples compacted to various saturations; and (iii) an instrumented Tempe cell approach affording concurrent measurement of λ(S) and the soil-water characteristic curve (SWCC). Dryout curves were obtained using each approach for F-75 Ottawa sand, a poorly-graded river sand, and a mixture of spherical glass beads. Conductivity sharply decreased at a critical saturation between 0.05 and 0.15 for all three materials. The single-sample approach required the longest time to produce a dryout curve (~500 hours) and resulted in λ values ~10% to 20% higher than the other approaches, an observation attributed to the presence of a sharp drying front associated with the evaporation testing procedures. The multiple-sample approach required the least amount of time (~15 hours) but produced a relatively sparse data set and is limited by potential errors associated with variability in sample preparation. The instrumented Tempe cell approach required a moderate amount of time (~123 hours) but resulted in the most robust λ(S) function and clearly defined thermal regimes. A clear advantage of the Tempe cell approach is that the SWCC may also be obtained, as often required for modeling coupled heat and moisture transport in many geotechnical applications.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 teacher head, 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".