Validation of a wood combustion model for use in numerical fire modeling
Bibliographic record
Abstract
This paper presents a simplified wood combustion model that was developed using a cone calorimeter experiment. Then, the model was validated using another cone calorimeter experiment, an intermediate scale experiment (a wood crib) and a set of large scale experiments. The numerical model successfully reproduced the main characteristics of the cone calorimeter HRR curve; two distinct peaked separated by a semi flat HRR. In case of the intermediate scale test (the wood crib), the numerical model also successfully predicted the main characteristics of the experimental curve: a peak HRR value followed by a semi flat HRR followed by a gradual decay. The large scale experiments were compartment fire tests. Compartment fire validation cases were conducted by comparing numerical results with correlations derived from previous fire experiments. Numerical results were comparable to experimental results in terms of general trend of the HRR curve, duration of the fully developed HRR and the compartment fire temperature.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| 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".