Processing and Shape-Setting of Shape Memory Alloys for Small Satellite Antennas
Bibliographic record
Abstract
In this study, four different NiTi-based shape memory alloys (SMAs) compositions were processed, shape-set, and characterized to evaluate their effectiveness as SMA actuation component for satellite antennas. Three of the compositions were commercially available NiTi wires (90°C Flexinol® actuator NiTi wire and Confluent ADB SE508 NiTi wire), NiTi SM495 plates (ATI Specialty Alloys and Components) and the other composition was in house lab-produced NiTiCu plate. Different shape-setting techniques were performed such as pin and plate, fixtures and dies, and finally a sandwich fixture. The two most promising outcomes were the SE NiTi 508 wire and the NiTiCu plate. A SE NiTi 508 wire was first heat-treated at 550 °C for 3 hours and then it was shape-set at 450 °C for 30 min using a Cu tube which was previously deformed to the desired deployment curvature and fixed on a steel rig. The wire was kept inside the Cu tube during the shape-setting process to obtain the desired curvature. After shape-setting, the wire was thermally cycled multiple times. The results showed that the SE NiTi 508 wire was able to retain its deployment shape successfully after each thermal cycle. Furthermore, a NiTiCu plate was sandwiched between two steel sheets which were shaped into the desired full-deployment shape beforehand. The NiTiCu plate was shape-set at 450 °C for 30 min and then thermally cycled multiple times to test its effectiveness. The NiTiCu plate retained its full-deployment shape successfully after every thermal cycle.
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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 | 0.001 |
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".