Low-Velocity Impact Response and Expe rimental Optimization of Modified Fiber Metal Laminates with Integrated Mechanical Interlock Bonding System
Bibliographic record
Abstract
This paper presents a modified version of fiber metal laminates with integrated mechanical interlock bonding system for aerospace applications.Sheet metals of Al 2024-T3 with surface machined infinitesimal hooks are used along with impregnated glass fiber composites to manufacture a modified version of GLAss REinforced aluminum (GLARE).Low-velocity impact responses of the modified GLARE is examined using a drop weight impact testing machine at an impact energy of 7.5 J.To optimize the geometry of the machined hooks to maximize the modified GLARE low-velocity impact resistance, we developed and tested four configurations of modified GLARE with four variants of hooks' geometry, including two hook sizes, namely, nano and micro and two hook profiles, namely, curved and straight.Impact tests show that modified GLARE with Straight Nano Hooks (SNH) have comparable dynamic responses to the standard GLARE (without hooks), while experiencing much less delamination and fiber damage.Microscopic inspection of the four configurations of modified GLARE also illustrates that SNHs generate modified GLARE with minimal manufacturing defects.The results obtained indicate that SNH is the optimum hook geometry for the development of modified GLARE.It can be considered as an alternative surface treatment for sheet metals in FML development process as it offers a modified version of the material with comparable impact responses to those manufactured by the industrial standard methodology but at a fraction of production cost.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".