Application of planar auto-compensating laser-induced incandescence to low-sooting turbulent flames and investigation of the detection gate width effect
Bibliographic record
Abstract
Laser-induced incandescence (LII) is an optical technique that is widely used for the in situ measurement of the soot volume fraction in flames. The low intensity of LII signals in low-sooting turbulent flames means that long camera acquisition times are needed to achieve sufficiently high signal-to-noise ratios. The direct application of auto-compensating LII (AC-LII) to infer the soot volume fraction from the measured LII signals can lead to large errors due to the significant decrease in the temperature of the soot particles over the duration of the camera gate. In order to reduce the measurement errors from AC-LII, we propose an improved approach in which the cooling of soot particles during the camera acquisition of LII signals is considered. The proposed methodology is applied to planar AC-LII measurements for the determination of soot volume fraction and primary particle diameter in a low-sooting turbulent flame, with the help of the open source LII software LIISim. This study represents the first application of planar AC-LII to a turbulent flame. A sensitivity analysis is also conducted in order to determine the main factors affecting the uncertainty of the proposed approach.Copyright © 2021 American Association for Aerosol Research
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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 | 0.001 |
| 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".