Soot Volume Fraction Measurements by Auto-Compensating Laser-Induced Incandescence in Diffusion Flames Generated by Ethylene Pool Fire
Bibliographic record
Abstract
The main characteristics of pool fire flames are flame height, air entrainment, pulsation of the flame, formation and properties of soot particles, mass burning rate, radiation feedback to the pool surface, and the amount of pollutants including soot released to the environment. In this type of buoyancy controlled flames, the soot content produced and their subsequent thermal radiation feedback to the pool surface are key to determine the self-sustainability of the flame, their mass burning rate and the heat release rate. The accurate characterization of these flames is an involved task, specially for modelers due to the difficulty of imposing adequate boundary conditions. For this reason, efforts are being made to design experimental campaigns with well-controlled conditions for their reliable repeatability, reproducibility and replicability. In this work, we characterized the production of soot in a surrogate pool fire. This is emulated by a bench-scale porous burner fueled with pure ethylene burning in still air. The flame stability was characterized with high temporal and spatial resolution by using a CMOS camera and a fast photodiode. The results show that the flame exhibit a time-varying propagation behavior with a periodic separation of the reactive zone. Soot volume fraction distributions were measured at nine locations along the flame centerline from 20 to 100 mm above the burner exit using the auto-compensating laser-induced incandescence (AC-LII) technique. The mean, standard deviation and probability density function of soot volume fraction were determined. Soot volume fraction presents an increasing tendency with the height above the burner, in spite of a local decrease at 90 mm which is approximately the position separating the lower and attached portion of the flame from the higher more intermittent one. The results of this work provide a valuable data set for validating soot production models in pool fire configurations.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".