Microtomographic Analysis of Impact Damage in FRP Composite Laminates: A Comparative Study
Bibliographic record
Abstract
With the advancement of testing tools, the ability to characterize mechanical properties of fiber reinforced polymer (FRP) composites under extreme loading scenarios has allowed designers to use these materials in high-level applications more confidently. Conventionally, impact characterization of composite materials is studied via nondestructive techniques such as ultrasonic C-scanning, infrared thermography, X-ray, and acoustography. None of these techniques, however, enable 3D microscale visualization of the damage at different layers of composite laminates. In this paper, a 3D microtomographic technique has been employed to visualize and compare impact damage modes in a set of thermoplastic laminates. The test samples were made of commingled polypropylene (PP) and glass fibers with two different architectures, including the plain woven and unidirectional. Impact testing using a drop-weight tower, followed by postimpact four-point flexural testing and nondestructive tomographic analysis demonstrated a close relationship between the type of fibre architecture and the induced impact damage mechanisms and their extensions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".