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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".