Primary Research on Bionic Design of Multi-surface Solar Concentrator Based on the Flower Structure
Bibliographic record
Abstract
Plant can’t grow and reproduce without sunshine. Flowers have an inseparable relationship with sunshine as an important part of the plants. Most studies on the relationship of the plant and sunshine focus on the influence that sunshine reacts to plant, such as photosynthesis. However, there is no much more special attention on the relationship between flower structure and sunshine. Through the observation and comparison, the outlines of many flowers contour have some similarities with the solar concentrator. This paper delves into the relation between flower structure and light, in order to get the new ideas of designing solar concentrator.By means of extracting a contour line of flowers, their geometric structure models are got. Through simulation calculations of optical software, light-gathering performance of flowers is researched in the circumstance of different angle incident. Then based on researching the light-gathering process of the flowers, the innovative design ideas of bionics solar concentrators with excellent performance are presented. So in this way traditional thinking mode of single curve or surface used in solar concentrator design is expanded.Key words: flowers; bionic; solar concentrator
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".