Configuration optimization of dampers for adjacent buildings under seismic excitations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Passive coupling of adjacent structures is known to be an effective method to reduce undesirable vibrations and structural pounding effects. Past results have shown that reducing the number of dampers can considerably decrease the cost of implementation and does not significantly decrease the efficiency of the system. The main objective of this study was to find the optimal arrangement of a limited number of dampers to minimize interstorey drift. Five approaches to solving the resulting bi-level optimization problem are introduced and examined (exhaustive search, inserting dampers, inserting floors, locations of maximum relative velocity and a genetic algorithm) and the numerical efficiency of each method is examined. The results reveal that the inserting damper method is the most efficient and reliable method, particularly for tall structures. It was also found that increasing the number of dampers does not necessarily increase the efficiency of the system. In fact, increasing the number of dampers can exacerbate the dynamic response of the system.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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