The mechanism of detonation attenuation by a porous medium and its subsequent re-initiation
Bibliographic record
Abstract
The attenuation and re-initiation mechanism of detonations transmitted through a porous section consisting of a two-dimensional array of staggered cylinders was investigated experimentally and numerically for acetylene–oxygen mixtures. It was found that the leading order attenuation mechanism is the wave diffraction around the cylinders. The local re-amplification permitting the self-propagation of the wave was due to wave reflections from adjacent obstacles. The critical conditions for transmittance of a detonation wave were found to correspond approximately to a pore size equal to approximately 30–60 detonation induction lengths, or one to two cell sizes. For quenched detonations, the re-initiation mechanism was found to rely on wave reflections from neighbouring pores. Depending on the mixture sensitivity, one or several shock reflections may be necessary to re-amplify the attenuated detonation wave back to a self-sustained wave. For the latter case, a novel mechanism was identified, where each shock reflection gives rise to a significant enhancement of the gas reactivity and burnout of large portions of unreacted gas. This leads to a slow acceleration of the leading front, punctuated by small-scale local sudden re-accelerations. The resulting wave interactions give rise to a topologically complex reaction zone structure consisting of alternating layers of reacted and unreacted gas. The role of turbulent diffusive burning during this transient is discussed.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 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".