Investigation on the Calibration of Numerical Models for Cast Steel Replaceable Modular Yielding Links in Steel Eccentrically Braced Frames
Why this work is in the frame
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Bibliographic record
Abstract
ABSTRACT A new generation of yielding links, referred to as cast steel replaceable modular yielding links (CMLs), was recently validated through extensive large‐scale testing, to enhance the seismic performance of steel eccentrically braced frames (EBFs). The effective use of CMLs relies on accurately evaluating the seismic response of the EBF systems, which requires robust calibration of the hysteretic model that simulates the nonlinear behavior of CMLs. Calibration relevance (CR) is a recently developed metric to evaluate the effectiveness of calibration methods for hysteretic models in structural seismic analysis. This study aims to use CR evaluation to examine various calibration methods for CMLs, to understand the impact of different aspects in calibration and to offer recommendations for robust CML model calibration. The CR evaluation is conducted on two prototype EBF buildings with two and four stories. Two modeling approaches of CML with different fidelities are considered for the reference and simulation cases in the CR framework. Four quantification methods for calibration error, which serve as objective functions in optimizing hysteretic model parameters, are investigated. Additionally, both standardized and more realistic loading histories (LHs) are considered. For the hysteretic model that is used, it is found that LHs featuring smaller peak link rotations, ranging from 0.03 to 0.07 radians, lead to more accurate calibration overall. The reasoning for this observation is the limitation of the hysteretic models, which is explained in detail at the end.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it