Simulation of Laser-Induced Incandescence Measurements in an Anisotropically Scattering Aerosol Through Backward Monte Carlo
Bibliographic record
Abstract
Laser-induced incandescence (LII) measurements carried out in aerosols having a large particle volume fraction must be corrected to account for extinction between the energized aerosol particles and the detector, called signal trapping. While standard correction techniques have been developed for signal trapping by absorption, the effect of scattering on LII measurements requires further investigation, particularly the case of highly anisotropic scattering and along a path of relatively large optical thickness. This paper examines this phenomenon in an aerosol containing highly aggregated soot particles by simulating LII signals using a backward Monte Carlo analysis; these signals are then used to recover the soot particle temperature and soot volume fraction. The results show that inscattered radiation is a substantial component of the LII signal under high soot loading conditions, which can strongly influence properties derived from these measurements. Correction techniques based on Bouguer’s law are shown to be effective in mitigating the effect of scatter on the LII signals.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".