Seismic response evaluation of a five‐story buckling‐restrained braced frame using multi‐element pseudo‐dynamic hybrid simulations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Nonlinear time history analysis relies on accurate modeling of the critical structural components and their complex interaction with the structure. Previous research indicates that calibration of numerical models can be affected by several factors, including the loading protocols. It is, therefore, critical to study previously developed and calibrated numerical models under more realistic loading histories, and determine whether the calibration process, loading protocols, and the numerical model themselves are adequate for achieving the desired level of accuracy. High fidelity benchmark system‐level experimental‐based simulation results could allow for a more holistic assessment of such questions. The University of Toronto Ten Element Hybrid Simulation Platform (UT10) was developed to produce such benchmark test results using hybrid simulations with multiple experimental elements subjected to realistic earthquake loads. This paper presents the first such experiment in the UT10 with multi‐element and single‐element experimental hybrid simulations on a five‐story steel structure with buckling‐restrained braces, representative of systems with a stable yielding hysteretic response. An adjustable yielding brace system was developed to capture the response of buckling‐restrained braces’ yielding core. The implications of modeling choices, such as using commonly available models in BRBFs, are studied. The experimental results are then presented and compared with numerical results. The limitations of existing models are identified. Such experimental results can be used by subsequent studies to improve the calibration of numerical models and allow for the development of more robust models, while also justifying the need for new loading protocols that could be used in the calibration process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.000 | 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 it