Full-Scale Tests of Gapped-Inclined Bracing System: Seismic Retrofit for Soft-Story Buildings
Bibliographic record
Abstract
This paper presents the results of full-scale experimental validations of the gapped-inclined bracing (GIB) system, a novel structural device for the seismic retrofit of soft-story buildings. The experiment consisted of three phases. Phase I tested a single brace to investigate its constructability and characterize its component-level performance. The second and third phases compared the reversed-cyclic response of two full-scale RC single-bay, single-story frames representing the soft story of a six-story RC frame: a conventional frame and the same frame retrofitted with GIBs. With the results observed from Phase I, the design considerations and constructability of the GIB system were improved for Phase III. The results of Phases II and III demonstrate that the GIB system significantly increases the lateral drift capacity of the RC frame, shifting strength degradation from ±1.5% for the original frame to more than ±4.0% drift for the retrofitted frame. In addition, even after considerable damage to the columns, the retrofitted frame was able to undergo repeated cycles of up to 7.0% drift without compromising its gravity load-bearing capacity, revealing that the damaged frame develops a stable GIB-only rocking response for large drifts.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".