Finite Element Modeling of Shape Memory Alloy Composite Actuators: Theory and Experiment
Bibliographic record
Abstract
The present paper proposes a non-linear finite element model for the time response of a novel shape memory alloy (SMA) actuator. The actuator has a plane beam configuration composed of a matrix material with SMA sheets or wires embedded in and/or bonded to the matrix part. The finite element model can be used to analyze both active and passive (with or without heating activation) responses of this kind of actuators. Due to large shear stresses and deformations, the model is developed based on a higher order shear deformation beam theory together with the von-Karman strain field. A one-dimensional constitutive equation with non-constant material functions together with sinusoidal phase transformation kinetics is used for the thermo-mechanical behavior of the SMA actuator. The constitutive and phase transformation kinetic equations make distinction between the stress-induced and temperature-induced martensite fractions. To evaluate the model, the fabrication of a prototype SMA composite actuator for conducting experiments is briefly described and the experimental work performed on the prototype actuator is presented. The test results are compared with the finite element numerical results. A good agreement between the finite element and experimental results corroborate the nonlinear finite element modeling approach.
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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 | 0.001 |
| 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 | 0.001 |
| 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".