Network Study of Plant Leaf Topological Pattern and Mechanical Property and its Application
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In order to explore the compliance structure and adaptability of the vein pattern of plant leaf, five fresh and mature leaf samples, which represent the typical leaf network in nature, are collected, and the finite element model of the samples are established and simulated. The results show that the topological pattern of plant leaf is self-adaptive to the multi-load fields. When considering the change of wind loads, it is found that the main vein consistently remains unchanged, and the lateral vein changes slightly along different wind load direction. Inspired by the similar work environment and structure, the bionic methodology of wind turbine blade is developed in this paper. Firstly, the wind turbine blade structure is optimized by using SIMP method. The results indicate that material distribution of wind turbine blade is similar to the leaf vein, where, the spar cap of the blade is equivalent to the main vein of leaf, and the skins are correspond to the lateral vein of leaf. Secondly, considering the similar stress environment, such as random wind loads, rain, snow, and self-weight, the topology structure of wind turbine blade was decided by referring the natural structure. Finally, the bionic method is used to design the spar cap region of the blade. The results show that the best fatigue life appears in blades with the ply angle in the range between 45° and 65°. It is not only coincident with the side vein angle of most plant leaves, but efficiently improves the blade fatigue performance.Keywords: Plant Leaf; Medial Axis; Self-Adaptability; Wind Turbine Blade; Bionic Design
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it