Guarded hot plate, optical scanning, transient divided bar: comparison of steady-state and transient methods to assess rock thermal conductivity.
Bibliographic record
Abstract
Thermal conductivity of rocks is a key parameter to model and design both deep and shallow geothermal systems relying on heat transfer simulations. However, in most cases, these models are based on literature data or laboratory measurements with high or unknown uncertainty. Three different laboratory techniques were compared in this work, trying to better understand analysis discrepancy related to the guarded hot plate, the optical scanning and the transient divided bar methods. The first method allows to assess thermal conductivity in steady-state when temperature equilibrium is reached in a small core sample placed between two parallel thermoelectric Peltier elements. The optical scanning technology adopts a moving infrared heat source and temperature sensors to scan diamond cut rock surfaces and thermal conductivity is measured in transient conditions at room temperature. The transient divided bar is a recent modification of the conventional steady-state apparatus and consists of two copper blocks of known conductivity, between which the specimen is interposed. By cooling the lower block with a thermostatic bath, the conductivity is derived from the rate at which the heat leaves the upper block. Rock specimens from two sites in Kuujjuaq (Québec) and Bergen (Norway) were collected to characterize the underground and to evaluate the efficiency of both deep and shallow geothermal systems. The Kuujjuaq samples belong to the Southeastern Churchill Province (1.8 Ga) and the Bergen ones to the Minor Bergen Arc (0.45 Ga). First results show the variability among the three devices ranging from 1 to 15%, with 7% average. The most representative value can be picked depending on the quality of the specimen and knowing advantages and limitations of each method.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".