Measurement of Temperature and Soot (KL) Distributions in Spray Flames of Diesel-Butanol Blends by Two-Color Method Using High-Speed RGB Video Camera
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Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">Taking advantages of high speed RGB video cameras, the two-color method can be implemented with a relatively simple setup to obtain the temporal development of the two dimensional temperature and soot (<i>KL</i>) distributions in a reacting diesel jet. However, several issues such as the selection of the two wavelengths, the role of bandpass filters, and the proper optical settings, etc. should be known to obtain a reliable measurement. This paper, at first, discusses about the uncertainties in the measurement of temperature and <i>KL</i> distributions in the diesel flame by the two-color method using the high speed RGB video camera. Since n-butanol, as an alternative renewable fuel, has the potential application in diesel engines, the characteristic of spray combustion of diesel-butanol blends under the diesel-like ambient conditions in a pre-burning constant-volume combustion chamber is studied. The Red and Blue channels of the high speed video camera are chosen for the two-color imaging because their response curve has a much smaller overlap. When adding the n-butanol into the neat diesel, the experimental result shows that the flame has a lower integral level for both flame temperature and soot density than neat diesel flame, owing to both increases in the fuel-borne oxygen and elongated ignition delays. In order to study the effect of LTC (Low Temperature Combustion), the ambient O<sub>2</sub> concentration is set at four levels: 21%, 18%, 15% and 12%. The results show that with the decrease of O<sub>2</sub> concentration, the flame temperature has a dropping tendency, while the <i>KL</i> (soot density) factor has a complicated behavior as a result of soot oxidation rate variation.</div></div>
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 it