Simplified design procedure for nonconventional multiple tuned mass damper and experimental validation
Bibliographic record
Abstract
Summary A simplified design procedure, for nonconventional multiple tuned mass damper (TMD) (NC‐MTMD) system, was proposed. This system entails targeted tuning of each TMD by considering several mechanical factors (e.g., seismic excitation, TMD mass, and location). Subsequently, all TMDs are tuned to their corresponding modes by a group of semi‐empirical design formulae based on previous theoretical studies on MTMD systems, in the tuning phase. The procedure was then calibrated by numerical optimization results of an actual existing thermal power plant structure and validated in both comparative numerical study and a shaking table test. The experimental model was designed based on the thermal power plant structure configuration. Springs and eddy current dampers were adopted to model the resistance and energy dissipation of TMDs. A numerical comparative study was carried out between a traditional design method and the proposed design scheme. Six representative NC‐MTMD mass cases were investigated in the shaking table test to study the robustness of the method. The seismic mitigation efficiency was evaluated by comparison study on frequency, peak, and root mean square responses. The NC‐MTMD design was proved to be effective to help reduce seismic responses of the structure.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".