Design, manufacturing, and performance evaluation of a novel smart roller bearing equipped with shape memory alloy wires
Bibliographic record
Abstract
Abstract In this study, a new type of seismic isolation device, called shape memory alloy (SMA) wire-based roller bearing (SMA-RB) is developed and introduced. The SMA-RB has been designed, manufactured, and experimentally tested. This bearing consists of cylindrical roller bearings and SMA wires with straight or cross configurations, as supplementary damping elements. In such a smart bearing, the superelastic (SE) SMA wires are passed through the hooks/pulleys attached to the supporting plates of the bearings in different configurations. The rollers provide lateral flexibility, and SMA wires supply energy dissipation and self-centering (SC) properties. In the manufacturing stage, a new mechanism for coupling wires (i.e. SMA wire joiner/coupler) is proposed. The results show that SMA wires, made of nickle titanium (NiTi), provide a SC damping mechanism with almost zero residual deformation which can effectively control the device from over-displacement. While using pulleys and newly designed wire joiners in the SMA-RB, the bearing can experience a stable cyclic behavior. Since the rollers generate a negligible amount of frictional force, the SE NiTi wires with a flag-shaped hysteresis mainly contribute to the overall shear hysteretic response of the SMA-RB. A triangular-shaped constitutive model can be used to accurately describe the hysteretic behavior of SMA-RB with different wire configurations.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".