Effect of reaction order on stability of planar detonation waves
Bibliographic record
Abstract
We examine the multi-dimensional linear and non-linear stability of planar detonation waves for one-step Arrhenius rate with arbitrary reaction order. A normal mode analysis with an iterative shooting method is used in linear stability. Results show that the effect of decreasing the reaction order is roughly equivalent to increasing the activation energy, or decreasing the heat release and overdrive. Both the one- and two-dimensional linear stability spectra consist of a larger number of unstable modes at lower reaction order. Bifurcation to non-oscillatory modes occurs at slightly lower activation energy or higher heat release and overdrive for lower reaction order. Thus overall, a lower reaction order results in more unstable waves. Numerical simulations, using a Weighted Essentially Non-Oscillatory scheme, show that activation energy has a stronger effect on cell regularity than the reaction order. It has been suggested that a relationship may exist between transverse wavelength from multi-dimensional linear stability analysis and cell sizes. Our computations confirm previous numerical results that show that the most unstable transverse wavelengths from linear stability analysis are comparable with the minimum channel width in which one full cell is observed in numerical simulations. Wider computations show that cells, which appear regular and periodic in narrow channel computations, become irregular. The average cell size approaches a consistent limit corresponding to an even larger size.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".