Comparison of Firebrand Propagation Prediction by a Plume Model and a Coupled–Fire/Atmosphere Large–Eddy Simulator
Why this work is in the frame
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Bibliographic record
Abstract
Firebrand spotting is one of the most vexing problems associated with wildland fires, challenging the lives and efforts of fire–fighting planners. This work is an effort to model numerically the event of firebrand spotting for the purposes of reviewing past modelling approaches and of demonstrating a more current coupled fire/atmosphere approach. A simple, two–dimensional treatment of the process of firebrand lofting is examined under the restrictive conditions typical of a classical plume modelling approach. Using this approach, the differences in trajectories of combusting and non–combusting particles are investigated. Next, firebrand spotting is examined using a coupled fire/atmosphere LES (Large Eddy Simulator) in which the processes of firebrand lofting, propagation, and deposition are connected. The behaviour of combusting and non‐combusting firebrands released from a moving grassfire into three‐dimensional time‐varying coupled atmosphere‐wildfire induced circulations is examined. When these results are compared to the results of a classical plume model for firebrand spotting, it is found that firebrand propagation in the coupled LES simulated flow is significantly different from that obtained by the two–dimensional empirically–derived plume model approach. The coupled atmosphere‐wildfire LES results are explorative and need to be subjected to direct testing.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it