Effects of Combustion Regimes on Localized Forced Ignition of Turbulent Stratified Mixture
Bibliographic record
Abstract
Localized forced ignition of turbulent stratified mixtures (〈〉 = 1, ′ = 0.2) with different values of mixture inhomogeneity has been analyzed based on Direct Numerical Simulations (DNS) for different values of Karlovitz number (𝐾𝑎) corresponding to the premixed turbulent combustion regime diagram.The initial values of turbulent fluctuations (i.e.𝑢'/𝑆 𝑏( = 1) ) and the integral length scale of turbulence (i.e.𝐿 11 /𝑙 𝑓 ) have been modified to bring about the change in 𝐾𝑎.The localized ignition is accounted by a source term in the energy transport equation which deposits energy over a specified time interval.It has been found that combustion takes place predominantly under a premixed mode of combustion following successful ignition.The percentage of heat release due to a premixed mode of combustion increases with increasing 𝐾𝑎 due to high mixing rate.An increase in 𝐾𝑎 has been shown to have adverse effects on the burned gas mass.The different level of mixture inhomogeneity shown to have favorable effect with increasing 𝐾𝑎 for sustaining combustion.Furthermore, a stratified combustion mixture has been found to be a more favorable choice over homogeneous mixtures for a given turbulent flow condition for sustaining combustion.
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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 | 0.001 |
| 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".