Application of shape memory alloy actuators in shape correction of composite radio telescope reflector surfaces
Bibliographic record
Abstract
Composite reflector based radio telescopes are next generation instruments for radio astronomical observation which provide several benefits over traditional metal-based radio telescopes. These benefits include: improved thermal characteristics, increased surface efficiency, reduced structural weight, etc. One of the challenges in radio telescope design is maintaining the performance of the optical system throughout its operating range of elevation angles and temperature, and under the influence of wind forces. At lower frequencies, and for smaller sized dishes, this has typically meant making the structure as rigid as possible, while at higher frequencies and for larger telescopes the need for active structures is understood. Traditionally, to realize reflective surface shape correction, electric actuators such as screw jacks have been used on panelized elements which require additional support structures at a large cost in complexity and weight. Instead, shape memory alloy (SMA) wire actuators can be embedded in the composite reflectors to compensate for global and local shape changes. Maximum displacement achieved was 30 which reduced the surface RMS error by 10%. This new approach offers a very clean and simple solution (no moving parts, no support sub-structure required for actuators) which promises to be cheaper and also much lighter in weight.
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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".