Seismic Response of Reinforced Concrete Frame-Shear Wall Structure with Metal Rubber-Based Damper in Coupling Beam
Bibliographic record
Abstract
In reinforced concrete (RC) frame-shear wall structure, the coupling beam needs to yield before the wall limbs are damaged, in order to dissipate the energy of the external load. However, the coupling beam has a limited energy dissipation capacity. Once severely damaged, the coupling beam is difficult to be repaired, which hinders the structural recovery after an earthquake. Considering excellence of metal rubber (MR) in hysteresis energy dissipation and deformation self-reset, this paper changes the energy dissipation mode of the coupling beam by adding an MR damper to the beam. Firstly, the stress-strain curve of MR was obtained through mechanical experiments, and used to construct the constitutive model of the material. Then, the parameters of the damper were designed based on the constitutive model. Next, the MR dampers were installed on the coupling beams of a 12-layer RC frame-shear wall structure. The authors analyzed the time histories of the elastoplastic dynamics of the structure under seismic actions, and calculated the seismic responses like interlayer displacement, absolute acceleration, and base shear force. These parameters were compared with those of the structure without the damper, and the output-deformation envelope curve of the damper on each layer were obtained. In this way, the authors studied how the parameters of the MR damper affect the seismic response of RC frame-shear wall structure. The results show that adding the MR damper to coupling beam can effectively weaken the seismic response of the RC frame-shear wall 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 | 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".