Deformation and Rupture of Thin Steel Plates due to Cumulative Loading from Underwater Shock and Bubble Collapse
Bibliographic record
Abstract
The damage sustained by rigidly-clamped square steel plates when subjected to close-proximity underwater explosions has been investigated. The test specimens consisted of plates 0.76 mm and 1.21 mm thick made of either ASTM A1008 mild steel or 350 WT structural-grade steel with a low-temperature notch-toughness requirement. The explosively-loaded area of the plates was square, with dimensions of 254 mm X 254 mm. High-explosive charges from 1.1 g to 50 g were used at different standoff distances to obtain different shock strengths and bubble collapse intensities. Although the main impulsive load on the plate was due to the shock impact, because the standoff distances were less than twice the maximum free-field bubble radius, a strong interaction between the detonation product bubble and the target plate caused a rapid water jet to impinge on the plate, resulting in additional loading and damage. As a result, four main regimes of loading and damage were identified: a) holing/petaling due to shock loading, b) edge tearing due to shock loading only, c) edge tearing due to the cumulative loading from shock and bubble collapse, and d) large deformation due to shock and bubble collapse loading. The damage mechanisms and dynamic response of the plates were measured using dynamic displacement sensors, pressure gauges, and high-speed video. A fracture analysis was performed on the damaged plates to analyze the mechanisms of failure. Finally, finite-element analysis using a failure criterion based on normalized shear stress and effective strain has been used to examine the failure limits.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".