Development of a Shape Memory Alloy-based Micro-Flow Effector for Missile Side Force Control
Bibliographic record
Abstract
Actuation systems for aerovehicles have traditionally been based on hydraulic or electromechanical systems because large control surfaces are needed to generate sufficient control authority. Active flow control systems rely on the ability of small flow effectors to trigger or stabilize flow structures to generate aerodynamic forces. In a previous study, wind tunnel tests showed that a proportional side force magnitude could be obtained by indexing static micro-flow effectors at various angular positions on the model nose. To develop a dynamic micro-flow effector assembly that would fit in the available missile model nose volume, shape memory alloy (SMA) wire was selected as an actuation material due to its force and displacement characteristics. A compliant link was designed to act as a transmission between the SMA actuator and the micro-flow effector. The performance of the SMA-actuated micro-flow effector was first evaluated under open-loop conditions. The results from a hybrid SMA model based on microstructural modeling and macroscopic phase kinetics compared well with the experimental data. The dynamics of the actuated micro-flow effector was characterized through a system identification technique. A two-step variable structure controller was synthesized using experimental data to obtain flow effector tip position control. Closed-loop test results showed that the control law was capable of providing effective control up to 0.5 Hz. An actuator assembly consisting of four SMAactuated micro-flow effectors was built and installed in the nose cone of a wind tunnel missile model. Results showed that good position control of the flow effector tip was maintained under wind-on and wind-off condition. The wind tunnel data showed that the side force was a nonlinear function of the flow effector deployment height. Positive or negative side forces were generated by actuating the port-side or starboard-side, respectively, micro-flow effectors located on the missile nose cone.
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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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".