Seismic performance of concrete-filled steel tube columns using ultra-high-strength steel under long-period ground motion demands
Bibliographic record
Abstract
The long-period ground motions observed in recent subduction-zone earthquake events (e.g., 2011 Tohoku earthquake in Japan) have subjected high-rise buildings to large numbers of lateral cyclic deformations. Concrete-filled steel tube (CFT) columns, which are often utilized in high-rise buildings in Japan, have been studied under lateral demands with a few loading cycles. However, their seismic performance under a larger number of repeated loading cycles is a considerable concern for future seismic events. Moreover, the use of ultra-high-strength steel materials in CFT columns has recently gained popularity. However, studies on CFT columns made using ultra-high-strength steel materials are still limited. In this study, the seismic performance of CFT columns made using conventional steel or ultra-high-strength steel were investigated experimentally under repeated lateral loading cycles. Four cantilever CFT column specimens were tested with a combined constant compressive axial loading and cyclic symmetric lateral loading. Each specimen was tested with two different lateral loading protocols: the conventional protocol with two cycles at each drift amplitude level, and a second protocol with twenty cycles at each amplitude level to represent the lateral drift demand under a long-period ground motion. The effects of the number of loading cycles on the seismic performance of the CFT columns are discussed. Based on the experimental observations, design recommendations are also presented. Moreover, an approach is proposed to estimate the onset of local buckling of the CFT columns under seismic loading.
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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 | 0.001 |
| 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 | 0.000 | 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".