The Influence of Spatial Discreteness on the Thermo-Diffusive Instability of Flame Propagation with Infinite Lewis Number
Bibliographic record
Abstract
The dynamics of flame propagation in systems with infinite Lewis number and spatially discretized sources of heat release is examined, which is applicable to the combustion of suspensions of fuel particles in air. The system is analyzed numerically using a one-dimensional heat equation with a source term for the reaction progress variable, which is specified to have zero diffusivity, and the model reveals a spectrum of flame-propagation regimes. For the case of a switch-type reaction rate and homogeneous media (continuous regime), the flame propagates steadily at a velocity in agreement with analytical solutions. As the sources are spatially concentrated into δ-function-like sources, propagation approaches the discrete regime with a fixed period between ignition of the sources, for which an analytic solution is also available for validation. When the source term is governed by an Arrhenius rate and the activation energy is increased beyond the stability boundary, the flame begins to exhibit a long-wavelength (4-5 times the thermal flame thickness) oscillation characteristic of the thermo-diffusive instability, in good agreement with prior stability analysis. When spatial discreteness is introduced, a competition is observed between the long-period oscillations of the thermo-diffusive instability and the pulsations associated with the rapid heat release of the concentrated sources. Interestingly, the presence of spatial discreteness is able to excite higher modes (period doubling and chaotic solutions) of the thermo-diffusive instability, suggesting that the introduction of discreteness may have an influence qualitatively similar to that of increasing activation energy. Relevance of the model parameters to experimental systems is then discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".