A variable property heat transfer model for predicting soil temperature profiles during simulated wildland fire conditions
Bibliographic record
Abstract
A numerical model of heat transfer in dry soil was developed to predict temperatures and depth of lethal heat penetration during cone calorimeter tests used to simulate wildland fire exposures. The model was used to compare predictions made using constant and temperature-dependent thermal properties with experimental results for samples of dry sand exposed to heat fluxes of 25, 50 and 75 kW m–2. Depths of lethal heat penetration predicted using temperature-dependent properties were within 2 to 10% of the values determined using measured temperatures, while predictions made using constant properties were within 10 to 21% of the experimental values. In both cases, predictions made by the model were within the 1-cm accuracy with which the depth of seeds and plant shoots in the soil can be determined in practice. The model generally over-predicted the depth of lethal heat penetration in dry or moist soil when temperature-dependent properties were used, and over-predicted the depth of lethal heat penetration in soils with a moisture content of greater than 10% if constant thermal properties were used.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".