Actuation of a lean-premixed flame by diffuse non-equilibrium nanosecond-pulsed plasma at atmospheric pressure
Bibliographic record
Abstract
This study investigates the effect of diffuse non-equilibrium nanosecond-pulsed plasma at atmospheric pressure on a lean-premixed CH4-air flame (ϕ = 0.65, P ∼ 0.3 kW). The domain of diffuse plasma existence is explored for both the case of the cold flow (no flame) and the case where a flame is stabilized downstream. The dynamics of plasma propagation and the flame displacement, following a high-voltage pulse, were measured using intensified charge-coupled device imaging. The energy of the plasma was measured using electrical probes and measurements of the second positive system of nitrogen were used to determine the rotational temperature and vibrational populations in the plasma. The effect of plasma on a flame was investigated by varying the pulse repetition frequency gradually from 1 to 7 kHz. Time-resolved imaging of the plasma emission shows that the primary streamer travels at higher velocities with increased pulsing frequency and with the presence of a flame ignited downstream of the discharge. Time-resolved imaging of the flame, following a high-voltage pulse, shows that the flame moves upstream into the unburned methane-air mixture with increased pulsing frequency. As the flame is displaced upstream, the nature of the discharge also changes, whereby less energy is coupled to the gas volume. Spectroscopic results reveal that the region in which the flame stabilizes is that of highest vibrational excitation and lowest rotational temperature. This actuation method is evidence of low-temperature chemical flame enhancement and potential control of a lean-premixed laminar flame at atmospheric pressure.
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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 | 0.000 | 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) | 0.001 | 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".