High spatiotemporal evolution of flame-droplet interactions in KHCO3 enhanced water mist fire suppression
Bibliographic record
Abstract
This study presents near-field measurements of potassium bicarbonate (KHCO 3 ) enhanced water mist suppression of buoyant turbulent fires, observing near-field interactions between water mist droplets and the turbulent flame front. The water mist is doped with varying concentrations of KHCO 3 , providing enhanced chemical fire suppression capabilities. Joint OH-PLIF and Mie scattering of droplets is employed with high spatial and temporal resolution (5000 Hz) to elucidate flame-droplet interactions resulting in extinction. A 20 kW turbulent buoyant diffusion flame is stabilised above the Sydney Turbulent Buoyant Fire Burner, surrounded by a water mist laden co-flow with droplet sizes d 32 ∼ 50 μm. The experimental operating conditions are chosen such that it is possible to delineate between the effects of increasing purely the inhibitor concentration and/or increasing the flow rate of water mist. Localised flame extinction and reconnection events are observed with increasing concentrations of KHCO 3 , demonstrating the opposing effects of radical pool depletion and edge flame propagation. The frequency of flame front breakages and thinning of the reaction front is also identified. Droplet positions in space relative to the flame front are quantified, showing distributions of droplet penetration depth from the air into the fuel side with increasing number of droplets traversing the flame front with increasing inhibitor concentration. A phenomenon known as droplet fragmentation is directly imaged, showing the explosive breakup of droplets doped with KHCO 3 .
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".