Morphing structural materials used in wind turbine blades
Bibliographic record
Abstract
With growing demands for cleaner and more sustainable energy, there has been rapid development in the wind energy industry. This trend has led to an increase in the size of wind turbines, which could cause drawbacks such as increased stresses, more complex control systems, and more costly manufacturing and transportation. Due to their high aerodynamic efficiency, light weight, and structural simplicity, morphing structures have become of great interest in the renewable energy industry. Morphing structures are structural systems capable of shifting their geometric form across two or more stable configurations to achieve targeted engineering functionalities. Despite having many advantageous characteristics, there is a significant challenge with designing morphing structures; that is, the structure must be compliant to demand low actuation force, while being stiff for load-carrying purposes. One approach to addressing this issue is using composite materials with anisotropic properties or bistable/multistable behavior. Through an extensive review of the recent literature, this study aims to provide insights into the underlying structural concepts and mechanical properties of morphing structural materials and their viability and sustainability for wind turbine blade applications. • Geometric characteristics and mechanical properties of morphing structures are reviewed and analyzed. • The viability and sustainability of morphing structures for wind turbine blade applications are investigated. • Structural materials and composites commonly used in modern turbine blades are described and discussed.
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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 | 0.001 |
| 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".