Refinement of the two-color pyrometry method for application in a direct injection diesel and natural gas compression-ignition engine
Why this work is in the frame
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Bibliographic record
Abstract
The soot emissions from internal combustion engines have significant health and environmental impacts and, as such, are subject to increasingly stringent regulations. Two-color pyrometry provides the in-cylinder soot cloud temperature and soot volume fraction and can provide insight to the in-cylinder soot formation and oxidation processes to guide research for reducing engine-out soot emissions. This work demonstrates improvements to the two-color pyrometry methodology, with a focus on low-temperature, low-soot regimes such as low-temperature combustion or combustion of direct injected natural gas. Through selection of a fast and robust numerical algorithm, characterizing and increasing the detection envelope, performing static and dynamic perspective adjustments, accounting for non-uniform and non-linear system response, as well as localized signal-to-noise ratio enhancement through image filtering, the performance of the pyrometric method was improved by a 40% increase in the resolved signal fraction. The refined two-color method was evaluated for both direct injected diesel and natural gas fueling strategies using a pilot-ignited direct injected natural gas fuel system and facilitated evaluation of local temperatures and soot concentrations in pilot-ignited direct injected natural gas combustion, despite the generally low soot levels in this combustion strategy.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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