Design of Protective Structures for Optimal Blast and Impact Mitigation.
Bibliographic record
Abstract
Design of blast-resistant and impact-resistant armor requires an understanding of how blast/impact load on structures look, how structures are damaged by blast/impact, and how the effects of blast/impact can be dissipated by the armor in an optimal manner. The focus of this dissertation is on these challenges to propose a systematic design approach for armor with optimal blast/impact mitigation capabilities. The objective is to study concurrently the mechanics of blast/impact, the mechanics of damage to structures due to blast/impact, and the mechanics of mitigating effectively the damaging features of blast/impact through the design of armor. The systematic design approach proposed in this research is missing in the solid mechanics literature in which the design of armor has used observation and experience rather than theory and optimization. In this dissertation, the contact/impact behavior of spherical shells with varying shell thickness to shell outer radius ratios has been investigated analytically and computationally to identify the major features of an impact pulse exerted on a structure. A simple dynamic model of the protected structure has also been developed to identify the features of a blast/impact responsible for the stress (damage) on the delicate target within the protected structure. These damaging features include both the peak pressure and the impulse delivered to the structure. This study examines how layers of elastic, plastic, and visco-elastic materials may be assembled to mitigate these features. The impedance mismatch between two elastic layers is known to reduce the pressure, but dissipation is required to mitigate the transmitted impulse in lightweight armor. A novel design concept called impact or blast tuning is introduced in which a multi-layered armor is used to tune the stress waves resulting from an impact or blast to specific frequencies that match the damping frequencies of visco-elastic layers. Moreover, the dimensionless material and geometrical parameters controlling the viscous dissipation of the energy within the armor are identified for a simplified one-dimensional system, to provide insight into how the optimal design of multi-use armor might be based on this concept.
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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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".