Enhancing the Capture of Two-dimensional, Shock-Induced Detonation Fronts using Harten’s Artificial Compression Method on Underresolved Cartesian Grids
Bibliographic record
Abstract
In the problems of detonation we are going to present here, the capture of shocks is crucial, since from its accuracy depends the very physical relevance of the whole solution. We already obtained some improvements in the capture of detonation fronts on underresolved grids in the one‐dimensional case thanks to Harten’s artificial compression [1], [2], and we now turn to two‐dimensional cartesian grids. In two space dimensions, the complexity of the discontinuity implies not only the location and speed of the front, but also its shape. These three aspects will be explored here, for the ZND detonation model, based on Euler’s system. We will use two‐dimensional central schemes for main computations, namely the classical “Lax‐Friedrichs” first order scheme and the second order “Jiang‐Tadmor” scheme [3]. To each of these methods, we will add two different versions of ACM (Artificial Compression Method), one that uses space splitting, and the other based on directional differencing [4]. Finally, as ACM require a good knowledge of the regions of the solution potentially carrying discontinuities, it will be assisted by a DoD (Detector of Discontinuities) based on the entropy production rate.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".