Comparison of the effect of one-way and two-way fire-wind coupling on the modelling of wildland fire propagation dynamics
Bibliographic record
Abstract
Operational wildland fire propagation models typically are uncoupled from the wind field or rely solely on estimations from an atmospheric model and/or meteorological observations. This leads to a frozen wind field with a high degree of uncertainty, and therefore to results drifting from the ground truth. On the other hand, a fully-coupled model is not viable for operational use due to the enormous computing effort required. This article proposes the use of real-time measurements from a drone swarm to enhance the results of a one-way coupled physics-based model (FireProM-F) to mimic the two-way coupling of fire and atmosphere. In the absence of actual measurements, synthetic data is used at the early stages of this research. The latter is generated using the WFDS levelset model with two-way fire-atmosphere coupling at various phases of the fire. Finally, the 'measured' wind field will be integrated into the target model to determine its effect on the outcomes.
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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) | 0.000 | 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) | 0.002 | 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".