Calibration techniques for quantitative NO measurement using Laser-Induced Fluorescence
Bibliographic record
Abstract
Laser-Induced Fluorescence (LIF) is an essential optical diagnostic technique for the high-resolution and low-uncertainty measurement of combustion species concentration in a variety of applications and conditions. Two different calibration techniques are explored in this study to obtain quantitative Nitric Oxide (NO) concentration measurements in flames. The first technique, the most employed in the literature, uses the extrapolation of the fluorescence signal from seeded to nascent NO and is only valid under negligible NO reburn conditions. The second technique uses the optical calibration of the experimental setup to relate it to a modelled LIF signal and can be applied regardless of NO reburn. Both of these techniques are explored under two different assumptions: constant and non-constant interfering LIF signal on the NO absorption spectrum. While the former is most often used in the literature, the latter is necessary when the LIF signal from interfering species cannot be distinguished from the NO-LIF signal, especially in high pressure conditions. Hence, a total of four techniques are presented in this work and are found to be in excellent agreement when performed in different flame conditions. The calibration techniques are applied to three lean, atmospheric, laminar, premixed, methane-air flames to explore their field of applicability. Specifically, the study explores the relevance of the techniques in reburn conditions, which occur mostly in high pressure, rich, highly-seeded, or NH 3 -containing flames. This study aims to offer the reader a portfolio of calibration techniques to use according to the conditions in which they need to be applied. While this study was carried out measuring NO concentration in a stagnation flame burner, the concepts and equations presented can be transposed to the measurement of other species and to other experimental configurations. • Comparative study of several NO-LIF calibration techniques. • Extrapolation of the signal from seeded to nascent NO is only valid in conditions of negligible reburn. • Calibration of the optical coefficient via modelling is valid in any flame condition.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".