Vibration Control of Buildings Using Magnetorheological Damper: A New Control Algorithm
Why this work is in the frame
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Bibliographic record
Abstract
This paper presents vibration control of a building model under earthquake loads. A magnetorheological (MR) damper is placed in the building between the first floor and ground for seismic response reduction. A new control algorithm to command the MR damper is proposed. The approach is inspired by a quasi-bang-bang controller; however, the proposed technique gives weights to control commands in a fashion that is similar to a fuzzy logic controller. Several control algorithms including decentralized bang-bang controller, Lyapunov controller, modulated homogeneous friction controller, maximum energy dissipation controller, and clipped-optimal controller are used for comparison. The new controller achieved the best reduction in maximum interstory drifts and maximum absolute accelerations over all the control algorithms presented. This reveals that the proposed controller with the MR damper is promising and may provide the best protection to the building and its contents.
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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) | 0.000 | 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