Prediction of Projectile Ricochet Behavior After Water Impact*
Bibliographic record
Abstract
Although not very common, forensic investigation related to projectile ricochet on water can be required when undesirable collateral damage occurs. Predicting the ricochet behavior of a projectile is challenging owing to numerous parameters involved: impact velocity, incident angle, projectile stability, angular velocity, etc. Ricochet characteristics of different projectiles (K50 BMG, 0.5-cal Ball M2, 0.5-cal AP-T C44, 7.62-mm Ball C21, and 5.56-mm Ball C77) were studied in a pool. The results are presented to assess projectile velocity after ricochet, ricochet angle, and projectile azimuth angle based on impact velocity or incident angle for each projectile type. The azimuth ranges show the highest variability at low postricochet velocity. The critical ricochet angles were ranging from 15 to 30°. The average ricochet angles for all projectiles were pretty close for all projectiles at 2.5 and 10° incident angles for the range of velocities studied.
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 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 | 0.001 |
| 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) | 0.001 | 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".