Multiphase flow simulation of ignition of solid explosive
Bibliographic record
Abstract
Ignition of a solid explosive involves chemical reaction, phase change, heat, mass and momentum transfers between the solid explosive and the product gas. To simulate the motion of the solid material Lagrangian method is needed to trace the deformation of the material. Calculation of the large deformation involved in the gas and the solid materials demands an Eulerian method to avoid mesh tangling issues that cripple conventional Lagrangian methods. To satisfy the demands for both Lagrangian and Eulerian methods, a particle-in-cell (PIC) method is adopted. While the method is computationally expensive compared to other numerical methods, it offers unique capability of combining the advantages of the Lagrangian and Eulerian treatments in handling material deformations. When the method is applied to multiphase flows, it can solve many complicated multi-material flow problems that are extremely difficult or impossible for other methods. Ignition of a solid explosive is such a problem. In the present paper we use a two-phase flow model based on available experimental data and commonly used momentum and thermal coupling models to investigate the ignition mechanisms and processes in a solid explosive material. Despite unresolved uncertainties in the model, results obtained are in qualitative agreements with experimental data.
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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) | 0.001 | 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".