A Numerical Study of the Effect of EGR on Flame Lift-off in n-Heptane Sprays Using a Novel PaSR Model Implemented in OpenFOAM
Bibliographic record
Abstract
<div class="section abstract"><div class="htmlview paragraph">The effect of exhaust gas recirculation (EGR) on flame lift-off in non-stationary n-heptane sprays was studied under Diesel engine-like conditions using numerical simulation involving complex chemistry and a novel partially stirred reactor (PaSR) model of subgrid turbulence-chemistry interaction.</div><div class="htmlview paragraph">The flame-stabilization mechanism is a result of complex physical and chemical interactions and cannot be described by a simplified theory. To leading order it is determined by the chemical reaction time at the leading edge, the turbulent diffusivity, and the flow velocity; so that there exists a balance between the local convection velocity and the triple-flame propagation speed. In this study of ignition and flame formation and stabilization processes, the VSB2 stochastic blob-and-bubble spray model was used in combination with the volume reactor fraction model (VRFM) implemented in OpenFOAM. The reacting volume fraction in the VRFM was determined by solving for mixture fraction, progress variable, and their variances in order to estimate the non-uniformities of the fluid cell; rather than simply taking the ratio of the mixing and chemistry time-scales. The chemistry is described by a reduced n-heptane mechanism with 36 species involved in 81 reactions.</div><div class="htmlview paragraph">The simulated lift-off trends are compared to available experimental data from the Engine Combustion Network, Sandia National Laboratories [<span class="xref">1</span>].</div></div>
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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 | 0.000 | 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) | 0.000 | 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".