Cyclic Behavior of a Novel MADAS Damper with No Axial Force and Improved Seismic Performance (Experimental, Numerical, and Analytical Assessment)
Bibliographic record
Abstract
Axial forces are generated in the plates of ADAS-yielding dampers when subjected to lateral loading due to their boundary conditions. This on one hand can lead to an increase in strain level of the plates and accelerate the damage process, while on the other hand, the interaction of the bending moment with the tensile axial force leads to increasing strength, which is undesirable in the performance of ductile members. In this paper, a modified ADAS device (MADAS) is introduced to prevent undesirable interaction of axial forces, and its cyclic behavior is evaluated both experimentally and numerically. To this end, in the first step, two test specimens with different number of connection pins were prepared and subjected to cyclic loading in a rigid frame. Experimental and numerical results have shown that due to the removal of the constraint in the vertical direction, the level of forces produced by the damper is almost constant and the X-shaped plates have been able to tolerate significant number of cycles before crack initiation. Afterwards, the cyclic performance of ADAS and MADAS dampers was numerically compared individually and also when placed in the frame. Furthermore, in the frame equipped with ADAS damper, the increase in the level of forces produced by the damper led to the buckling of the braces, while the level of generated forces was totally in the expected range in the frame equipped with MADAS damper.
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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 | 0.000 | 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 | 0.001 | 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 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".