Design of a Braided Composite Badminton Racket on Solidworks
Bibliographic record
Abstract
Current badminton rackets are typically made out of steel, aluminium, or carbon fibre. Although these materials perform acceptably, there are some downsides to their properties. However, these non-ideal characteristics of badminton rackets may be overcome with the usage of different manufacturing materials, specifically braided composites. An example of a braided material is KevlarⓇ. Kevlar is a heat resistant and high strength synthetic fibre that can be manufactured into braids using a maypole braiding system. These Kevlar braids can then be manipulated to a preferred shape for the curing process. In order to come up with a feasible design to base the prototype, a 3D modelling software (SolidWorksTM) is used. This ensures geometrical viability and possible to manufacture of the prototype. Modeling a badminton racket on Solidworks required the modelling of a racket head, and handle. The head was created using 2 ellipses, one of which acted as a skeleton, or mould for the Kevlar braid, and the other was a hollow ellipse which encompassed the mold and acted as the Kevlar braid. The solid ellipse was created in two halves, each having either an extrusion or a hole in the ends. This allowed them to easily attach to form a full ellipse. Once modeled, the solid ellipse was 3D printed to act as the curing mandrel, an internal skeleton for the Kevlar braids. In order to attach the head to the handle, a three-part connector piece was created and 3D printed. The rod of the racket was not created with an internal skeleton because the flexibility would falter. Instead, the Kevlar braids were slid off the material after curing and attached to the racket heads connector piece. In order to have a balanced weight ratio throughout the racket, the grip was created with an internal 3D printed skeleton. This structure allowed for a feasible, flexible, and strong Kevlar based product.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.015 | 0.005 |
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".