Characterizing the Two‐Dimensional Thermal Conductivity Distribution in a Sand and Gravel Aquifer
Bibliographic record
Abstract
Both hydrologic and thermal transport properties play a significant role in the movement of heat through permeable sedimentary material; however, the thermal conductivity is rarely characterized in detailed spatial resolution. As part of a study of the movement of thermal plumes through a sand and gravel aquifer, we have constructed a two‐dimensional profile of thermal conductivity. This work consisted of: (i) measuring the thermal conductivity of the soil solids, λ s , for the main stratigraphic units using the steady‐state divided‐bar apparatus and estimating conductivity from mineral composition; (ii) measuring the volumetric water content and porosity using crosshole ground‐penetrating radar; (iii) evaluating four models used to predict the apparent thermal conductivity, λ, of variably saturated soils and selecting the best model using the information‐theoretic approach, (iv) calculating the λ field on a 0.25‐m square cell grid using measured data and the selected model, and (v) simulating thermal transport within the two‐dimensional domain using a finite element numerical model. The apparent thermal conductivity in the saturated aquifer ranges from 2.14 to 2.69 W m −1 K −1 with a mean of 2.42 W m −1 K −1 Numerical simulations show that the heterogeneous thermal conductivity field results in increased thermal dispersion that is most pronounced at the plume front. Our values for λ and λ s may be used for glacial soils with similar mineralogy and texture. Our methods may also be used at other sites to construct the thermal conductivity distribution.
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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 | 0.001 | 0.002 |
| 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".