Geometric stability of detonation propagation in curved channels
Bibliographic record
Abstract
Abstract Detonation propagation dynamics in circularly curved channels are investigated using both experimental and geometric modeling approaches. Quasi-two-dimensional curved channels with a range of channel widths and curve radii were tested. Experimentally, three propagation modes were observed: a stable propagation mode featuring a flat detonation front and steady near-CJ propagation, an unstable mode with varying frontal structures and velocity oscillations, and failure to propagate. Experimental data from the current study and those in the literature show that for a given ratio between channel width and detonation cell width, there exists a critical inner-to-outer radius ratio that sets apart the stable and unstable propagation modes. A regime map is proposed in the present work to describe the observed propagation modes. The regime map highlights the competition between the focusing effect of the outer concave boundary (with respect to the transverse waves) and the diverging effect of the inner convex boundary in addition to the effect from the channel-to-cell width ratio. With a reduced channel-to-cell width ratio, the inner-to-outer radius ratio critical to sustained detonation propagation must increase. Geometric modeling results are found to be in agreement with experimental observations. In addition, geometric modeling was used to test channel geometries beyond what has been experimentally tested and to provide a rational explanation for the regime map.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".