Seismic design of self-centering rocking core-moment frames with extended displacement-based approach for higher modes
Bibliographic record
Abstract
This paper introduces a novel displacement-based design method specifically tailored for Rocking Core-Moment Frame (RCMF) archetypes. RCMFs integrate the self-centering capabilities of Rocking Cores (RCs) with the energy dissipation capacity of Repairable Moment Frames (RMFs). The proposed design procedure accurately estimates higher-mode demands, which are essential for the capacity design of RCMF members. It emphasizes predicting design forces, by appropriately allocating strength between RMFs and RCs using the cantilever beam analogy. Additionally, a fail-safe mechanism is introduced to the RCMF design, ensuring self-centering at the immediate occupancy level while preventing potential collapse at design level. To validate the proposed approach and analytical formulas, nonlinear dynamic analyses are conducted on RCMFs subjected to far-field ground motions. The procedure concludes with the seismic evaluation of illustrative archetypes, including buildings supported by pinned and stepping cores, with both single and coupled configurations. The outcomes demonstrate the efficiency of the proposed displacement-based design procedure for the rapid analysis and preliminary design of RCMFs. • RCMFs offer a sustainable solution by combining repairable MFs and rocking cores. • Proposing a tailored Displacement-Based Design method for RCMF archetypes. • Archetypes are designed to withstand seismic forces, including the effects of higher modes of vibration. • Validation of the method under 44 far-field ground motions. • Demonstrates efficiency in the rapid analysis and design of RCMFs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 teacher head, 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".