Development of thermoplastic composite cones for helicopter tail boom application
Bibliographic record
Abstract
Thermoplastic composites offer many attractive characteristics such as no shelf life, high fracture toughness, high temperature resistance, recyclability etc. The short coming of thermoplastic composites is their high viscosity, even at processing temperature. Due to the high viscosity, techniques for the manufacturing of thermoplastic composite have been limited to molding processes such as compression molding, high temperature stamping, where high temperature, high pressure and long duration are used. The advent of automated fiber placement machine brings forward possibilities to manufacture of large thermoplastic composite components. This is due to the fact that heating and compaction is done on the go directly on the surface of the substrate, and the flexibility of the feeding head to conform to the shape of the mold. It is in the spirit of exploration for new manufacturing possibilities that Bell Helicopter has supported an inter industry- university project for the development of thermoplastic composite cones aimed at helicopter tail boom applications. The cone represents a segment of the helicopter tail boom. It is made using carbon/PEEK material and automated fiber placement. The work consists of the Determination of the lay-up sequence to address the loads, the Development of the manufacturing processes, the Measurement of temperature variation during the making of a ring, the Checking of the quality of the cone, Development of tube bending test set up, Development of theoretical calculations to determine the buckling load of the cone subjected to bending, Testing the cone under bending load, and Comparing the experimental buckling with calculated buckling load.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".