Analysis of the deformation of conical shells made by 4D Printing of composites
Bibliographic record
Abstract
4D printing of composites (4DPC) is a technique that allows the manufacturing of composite structures to shape without the use of a complex-shaped mold. Instead, only a flat mold is utilized. This innovative technique has been employed to make composite leaf springs with performance comparable to metallic springs, omega stiffeners, and corrugated core for flexible wings. Recently, this technique was applied to fabricate composite conical shells. While experimental work has successfully demonstrated the transformation from flat to conical shape, the development of a numerical method to replicate this transformation is highly desirable. The availability of such method not only provides theoretical support for the experimental result, it also provides means to develop other shapes. The lay-up sequence for transforming flat to conical shapes involves curvilinear fibers. Most if not all finite elements currently available deal only with straight fibers (even though the boundaries of the element may be curved). The objective of this research is to examine the efficiency of the analysis for the deformation of composite from flat to curve made by 4DPC by special finite elements containing curved fibers. The developed finite elements were used to determine the shapes of conical shells made using multiple distinct lay-up sequences. The direction of bending in curvilinear fiber structures is significantly influenced by the orientation of the fibers. This highlights the critical role of fiber orientation and layer composition in achieving desired shapes in 4D printed composites.
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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) | 0.000 | 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 | 0.001 | 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".