Design and Analysis of Multi-Patch Composite Plates for a High Multi-Stability of a Morphing Skin
Bibliographic record
Abstract
The morphing structures are a significant research area in engineering industry, especially, the fields of aerospace and aircraft which aim at improving performance over a wider range of normal operating conditions. The most challenging design requirement of a morphing structure is a skin, which exhibits both in-plane compliance and out-of-plane stiffness. An asymmetric composite laminate is as good candidate for achieving a morphing skin. By curing the unidirectional composite laminate at elevated temperature and cooling at room temperature, a phenomenon of bi-stability is mainly caused by the mismatch in the thermal expansion coefficients of lamina within the laminate. In practical applications, a single bi- stable composite cannot fulfil multi-stable configurations required for a multifunctional surface. For this reason, a number of bi-stable composite laminates is connected together as continuous surface for showing a higher degree of multi-stability. In this dissertation, the model of Multi-Stable Composite Surface (MCS) is presented by tailoring bi-stable composite patches together in a (m×n) grid form, and then the model is extended to connect a mix of bi-stable and mono-stable composite patches. This new modification on the model reduced the interactions between adjacent bi-stable composite patches in order to show more distinct stable shapes. Based on these results, a novel connection approach is presented by introducing a flexible aluminum strip between connected bi-stable composite patches. This Multi-Stable Hybrid Surface (MHS) shows a theoretical maximum 2𝑛 stable configuration for 𝑛 number of bi-stable composite patches. These stable configurations are interesting shapes that may be used to create a large multi- stable surface as a useful device in a morphing skin application. Finally, potential applications of multi-stable hybrid surfaces are introduced. This work could be used as a guideline for design of a large multi-patch morphing skin in order to improve the multi- functional structures.
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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 | 0.001 |
| 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".