Self-Centering Energy Dissipative Bracing System for the Seismic Resistance of Structures: Development and Validation
Bibliographic record
Abstract
Buildings designed according to modern seismic codes are expected to develop a controlled ductile inelastic response during major earthquakes, implying extensive structural damage after a design level earthquake, along with possibly substantial residual deformations. To address this drawback of traditional yielding systems, a new bracing system that can undergo large axial deformations without structural damage while providing stable energy dissipation capacity and a restoring force has recently been developed. The proposed bracing member exhibits a repeatable flag-shaped hysteretic response with full recentering capabilities, therefore eliminating residual deformations. The mechanics of this new system are first explained, the equations governing its design and response are outlined, and one embodiment of the system, which combines a friction dissipative mechanism and Aramid tensioning elements, is further studied. Results from component tests, full-scale (reduced length) quasi-static axial tests, and quasi-static and dynamic seismic tests on a full-scale frame system are presented. Experimental results confirm the expected self-centering behavior of the self-centering energy dissipative (SCED) bracing system within the target design drift. Results also confirm the validity of the design and behavior equations that were developed. It is concluded that the proposed SCED concept can represent a viable alternative to current braced frame systems because of its attractive self-centering property and because the simplicity of the system allows it to be scaled to any desired strength level.
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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 | 0.001 | 0.001 |
| 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".