Experimental evaluation of bench-scale flammability of Ulex europaeus using a cone calorimeter
Bibliographic record
Abstract
Wildfires have been causing considerable damage worldwide, and improving the ability to predict wildfire behaviour will ensure effective emergency response and keep ecosystems and communities safe. Increasing the understanding of factors affecting vegetation flammability is necessary for improving fire behaviour prediction models. This work investigates the influence of moisture content on the flammability of live and dead needles (0-3mm), twigs (3.1-6mm) and stems (6.1-10mm) of gorse (Ulex europaeus L.). Gorse is a shrub invasive in New Zealand, Chile and Western United States. In these countries, gorse poses a fire risk to nearby communities, as it contains flammable volatile resins, accumulates a substantial amount of elevated dead material, and grows in large masses, all of which promote fire ignition and growth. Gorse flammability was quantified with a bench-scale oxygen consumption calorimeter (cone calorimeter) with a focus on heat release rate. Supporting tests were performed on small sub-samples using simultaneous thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC) to assess material-scale pyrolysis dynamics, providing fine scale information on the thermal degradation of each tissue type at the particle level. The experimental methodology included investigation of the maximum moisture content at which each tissue type can ignite at 50 kW/m2, which is a reasonable approximation of the heat flux at the vegetation surface during fire front arrival in a shrub fire. Six moisture content levels from zero to the highest ignitable moisture content were then selected, and samples were placed into a climate chamber to set the moisture content of the samples to the desired level. Three replicates of each tissue type were tested in a cone calorimeter at each moisture content. Flammability was assessed based on the heat release rate, effective heat of combustion, mass loss rate, time to ignition and flaming duration. Additionally, a small sub-sample of fresh live and dead needles, twigs and stems was analysed in the TGA/DSC apparatus. TGA/DSC results showed a different thermal degradation mechanism between dried live and dead fuel, with live tissue being more flammable than dead. However, the pyrolysis dynamics were not substantially affected by particle size, suggesting that the differences in flammability attributes measured in the cone calorimeter are likely driven by physical characteristics such as surface-area-to-volume ratio rather than chemical composition. The results of this work contribute to the understanding of gorse flammability and the effect of moisture content and fuel structure on fire behaviour.
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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 | 0.000 |
| 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) | 0.001 | 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".