Comparative Study of Energy Absorption Capability of Flat Plate Coupons Made by CFRP Plain Weave Fabric Composites
Bibliographic record
Abstract
Despite years of governmental and academic institutions’ researches, no experimental standards are established for evaluating crush Specific Energy Absorption SEA for plain weave fabric woven carbon-fiber-reinforced composites used in modern aircraft structures as elements of the boxes to mitigate damage during crush events. At the laboratory scale, this paper proposes a comparative study of energy absorption capability of flat plate coupons made by CFRP plain weave fabric composites. A new fixture design and setup were created with hydraulic pressure and drop tower machines to carry out tests of flat plate composite specimens under quasi-static and low velocity on-axis crash loading. For investigating parameters sensibility of triggers and layups, numerical and experimental results of four trigger types and three stacking sequences were compared. A confrontation between experimental and pre-developed UL-Crush numerical material model results confirms that coupons with 0˚ oriented central plies and saw teeth or corrugated triggers dissipates higher energy during crush, compared to coupons with 90˚ or 45˚ oriented central plies and chamfer 45˚ or steeple triggers. An efficient and simplified experimental methodology was developed to measure and investigate different parameters influencing SEA of composites under crush load. Comparison between experimental and UL-Crush material model confirms the performance of such simulation tool.
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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 | 0.001 | 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".