On the Placement of Active Bars and Optimal Feedback Gain in Random Adaptive Structures for Vibration Suppression
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Bibliographic record
Abstract
This paper addresses active vibration control of adaptive structures using piezoelectric active structural elements with built-in sensing and actuation function. Optimal placement and feedback gain of these active members are important issues, which are discussed in this study. An efficient optimal placement strategy has been developed using minimum control energy dissipating over infinite time interval. Optimal location of active members has been found through minimization of total control energy dissipating over infinite time interval using Simulated Annealing (SA) algorithm. Moreover, the effect of structural randomness and random load in optimal feedback gain has been investigated. To accomplish this, a mathematical model with reliability constraints on the stress and displacement is developed and the optimal velocity feedback gain of active members, using probabilistic optimization technique, is obtained. Illustrative examples are presented to demonstrate the effectiveness of this methodology. It is shown that deterministic approach can not provide reliable optimum design values.
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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