Phase based Control of a Novel Beam-Shape MRE-based Adaptive Tuned Vibration Absorber
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Bibliographic record
Abstract
Semi-active adaptive tuned vibration absorbers (SATVAs) can be effectively utilized to attenuate the unwanted vibrations in a broad range of tonal excitations. If the excitation frequency of the primary system changes with time, it is desirable to adaptively tune the natural frequency of the absorber to track the excitation frequency. To this end, the stiffness of the SATVA can be altered. The current study investigates the phase based control of a proposed MRE based beam-like structure as a semi-active adaptive tuned vibration absorber. The SATVA consists of a sandwich beam with MRE core layers constrained by thin elastic plates located on the top, bottom and also in the middle, as well as the electromagnets attached at the free end of the sandwich beam. The function of electromagnets is twofold: providing the required magnetic field to the MRE layers and also serving as the absorber’s active mass. Upon application of a controllable external magnetic field through the current applied to the electromagnets, the stiffness of the MRE layers and consequently the SATVA’s natural frequency can be controlled. In this study, first using the finite element dynamic modelling, an equivalent single-degree-of-freedom model of SATVA based on its fundamental mode of vibration has been derived. Then, using the variation of MRE’s shear modulus with respect to the applied magnetic field, the variation of the natural frequency of SATVA with respect to the applied magnetic field has been evaluated. Finally, a control law based on the phase difference between the relative accelerations of the absorber and host structure, has been utilized to evaluate the magnetic field required by the absorber to track the time varying tonal excitation. The performance of the control law is then demonstrated and compared with the passive system.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 it