A DNS Study of Turbulence Effects on Ignition in Stratified Combustible Mixtures
Bibliographic record
Abstract
Localised forced ignition (i.e. spark or laser) of turbulent stratified mixtures has been numerically analysed using three-dimensional Direct Numerical Simulations (DNS) for different level of turbulent intensities. The initial values of turbulent fluctuations and integral length scale of turbulence are modified to reflect different turbulent combustion regimes. The ignition is accounted by a source term in the energy transport equation which deposits energy over a specific time interval. It has been found that combustion takes place primarily in premixed mode of combustion following successful ignition. The percentage of heat release due to a premixed mode of combustion increases with increasing turbulent intensity due to higher rate of mixing. The effects of mixture inhomogeneity for a given turbulent intensity has favorable outcomes on sustaining combustion following successful ignition, however it has been found that an increase in turbulent intensity has adverse effects on the burned gas mass. Moreover the mixture inhomogeneity effect shows non-monotonic trends on burnt gas mass. The present DNS result shows that an increase in turbulent intensity leads to increase in Minimum Ignition Energy (MIE) (consistent with previous experimental findings). However, for a given realization of initial mixture distribution (휙), it has been found that stratified mixture to be more favorable over homogeneous mixture for a present turbulent flow condition for achieving a higher burning rate.
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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 | 0.001 | 0.003 |
| 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 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".