Seismic Retrofitting of Existing Steel Frames with External BRBs: Pseudo‐Dynamic Hybrid Testing and Numerical Parametric Analysis
Bibliographic record
Abstract
ABSTRACT The use of buckling‐restrained braces (BRBs) is an effective strategy for improving the seismic performance of existing structures. BRBs can be included within existing frames, creating an additional load path and contributing to their strength, stiffness, ductility, and, in turn, energy dissipation capacity. However, BRBs are typically inserted within the structural mesh of the existing frames, thus requiring the demolition and reconstruction of non‐structural components. The present study explores the seismic retrofitting of existing steel structures, considering an external placement of BRBs to minimize the invasiveness of the intervention scheme and, consequently, business interruptions and indirect losses. A two‐story steel moment‐resisting frame (MRF) designed primarily for gravity loads and retrofitted with BRBs placed externally to the frames were considered for case study purposes. The research includes large‐scale Pseudo‐Dynamic Hybrid tests performed as part of the HITFRAMES (i.e., HybrId Testing of an Existing Steel Frame with Infills under Multiple EarthquakeS) project funded by the EU‐H2020 SERA Consortium in Europe. The experimental results provided significant insights into the seismic response of the retrofitted structure and allowed the calibration of advanced 3D finite element models. An extensive numerical parametric analysis was performed to investigate some of the key variables affecting the local and global response of the structure. The results provide valuable insights into effectively implementing this retrofit solution and the influence of BRB eccentricity on the seismic response.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".