Steel flexure and shear yielding base‐mechanism for enhanced seismic resilience of RC core wall high‐rise structures
Bibliographic record
Abstract
As a result of rapid urbanization worldwide, there is an increasing demand for high‐rise buildings, creating an acute need for more resilient tall structures, especially in regions of high seismicity. One of the main challenges facing design engineers is that buildings become increasingly susceptible to higher‐mode effects as they become taller. Although current design practices typically achieve life‐safety and collapse‐prevention during major earthquake events, there is often extensive structural and non‐structural damage, in great part exacerbated by the contribution of higher‐mode responses. This article proposes a novel system involving a flexure and shear yielding base‐mechanism, designed to limit both the first mode and higher‐mode responses of a 42‐story benchmark structure. These concepts only make use of well‐defined buckling restrained steel braces, which have been extensively tested over many decades now and are currently implemented widely in buildings, to achieve the desired shear and flexural base yielding mechanisms. Nonlinear three‐dimensional (3D) models developed in ABAQUS were used to validate key elements while models of the benchmark structure and base‐mechanism were developed in ETABS to perform Nonlinear Time‐History Analyses (NLTHA) for three hazard levels to investigate the global seismic response of the proposed system. Improvements among key seismic response parameters are observed at all hazard levels. By concentrating inelastic demands in the dedicated base steel yielding braces in the proposed system, quick inspection and potential repair after a major earthquake can be achieved with reduced disruptions to the use and operation of the building above.
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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) | 0.002 | 0.001 |
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".