Retrieval of temperature and extinction coefficient from modulated absorption emission technique: Effects of practical light collection, self-absorption, in-scattering, and finite spatial resolution
Bibliographic record
Abstract
Light extinction and emission measurements in soot-laden flames have extensive application for axisymmetric fields where Abel inversion can de-convolve the radial field. The simplified treatment of the radiative transfer equation typically ignores the contributions from signal trapping, in-scattering, physical light collection systems, and finite spatial resolution. A backward Monte Carlo ray tracing methodology is implemented to gauge the validity of these assumptions for high pressure counterflow diffusion flames (CDFs) modelled as an axisymmetric, non-homogeneous, anisotropic, attenuating, and emitting media. Results show that the practical light collection angle is an important parameter with cot θ = α < 107 resulting in errors larger than 5% whereas the optical design in terms of telecentric and non-telecentric system has nominal effects. The in-scattering contributions are noted to be large for high pressure CDFs with measured extinction coefficients close to absorption coefficients at smaller wavelengths. Signal trapping is also larger for such flames and can cause ∼ 50 % reduction in recovered absolute radiance for λ = 650 nm . A correction methodology for signal trapping is proposed and is noted to recover the unattenuated signal, albeit with slight over-predictions. The temperature estimates using uncorrected radiance can under-predict actual temperatures by ∼ 150 K for the highly sooting flame while the corrected radiance over-predicts it by ∼ 25 K . Finite spatial resolution is also noted to cause a 23% reduction in peak extinction coefficients at λ = 900 nm , the error in which reduces with improved spatial resolution. Spectral disparity in spatial resolution also causes errors in temperature gradients and can over-predict the measured temperatures by ∼ 50 K . • Practical light collection can cause errors ( > 5%) in absorption and emission signals. • In-scattering contributions in high pressure CDFs result in κ e ≈ κ a . • Signal trapping in OD > 3 flame causes error of ∼ 50% in radiance and 150 K in temperature. • Proposed correction scheme recovers unattenuated signal with slight over-prediction. • Finite and disparate spatial resolution causes ∼ 50 K temperature error for OD > 3 flame.
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".