The relation between shock-state particle velocity and free surface velocity: A molecular dynamics study on single crystal Cu and silica glass
Bibliographic record
Abstract
We investigate the ratio Rrp of the free surface velocity to the shock-state particle velocity during shock wave loading with molecular dynamics simulations on two representative solids, single crystal Cu, and silica glass. The free surface velocity is obtained as a function of the particle velocity behind the shock front (or shock stress) for loading on Cu along ⟨100⟩, ⟨110⟩, and ⟨111⟩, and on the isotropic glass. Rrp≥1 for Cu and Rrp<1 for silica glass, and it increases with shock strength; the simulations agree well with the experimental results. For supported shock loading of silica glass at 30–90 GPa, the SiIV–SiVI transition occurs upon shock, inducing substantial densification and thus small Rrp (0.65–0.78). For single crystal Cu, Rrp deviates from 1 near the Hugoniot elastic limit and reaches ∼1.2 at 355 GPa for ⟨100⟩ shock. Rrp is anisotropic, e.g., it is about 1.02, 1.08, and 1.06 for shock loading to about 80 GPa along ⟨100⟩, ⟨110⟩, and ⟨111⟩, respectively. Such an anisotropy is mostly due to that in the degree of stress relaxation at low pressures and that in solid state disordering at high pressures. These results suggest that Rrp is materials dependent and the assumption of Rrp=1 is only valid in a limited stress range. Caution should be exercised when interpreting the free surface velocity measurements as regards the shock states.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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
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