Numerical Analysis of Binding Yarn Float Length for 3D Auxetic Structures
Bibliographic record
Abstract
Recently, the auxetic fabrics have gained much importance in the scientific and industrial community due to their excellent impact‐resistance property. Due to this property, they have several applications, including automotive, aerospace, and ballistic areas. The auxetic three‐dimensional (3D) woven fabrics are a less explored domain in the auxetic community. Herein, special attention is given to the numerical analysis of the 3D auxetic structure. The negative Poisson's ratio of 3D auxetic structures is studied using ANSYS workbench structural analysis module. The effect of binding yarn float length on negative Poisson's ratio is tested on ten different 3D orthogonal through the thickness structures with binding yarn float length of 1:1, 2:1, and 3:1. Furthermore, the effect of the number of binding yarns and the number of layers is also studied numerically. The results show that the auxeticity of the woven structure increases with increasing the number of binding yarns and their float length. Moreover, decreasing the number of layers from 3 to 1 increases the auxeticity.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".