Hybrid Simulation for Earthquake Response of Semirigid Partial-Strength Steel Frames
Bibliographic record
Abstract
The behavior of semirigid partial-strength connections has been investigated through either experimental component testing or detailed three-dimensional (3D) finite-element (FE) models of beam-column subassemblies. Previous experiments on semirigid partial-strength connections were conducted under idealized loads and boundary conditions, which do not represent real situations. In addition, the developed 3D FE models are computationally expensive and have primarily been used under monotonic loadings. Evaluating the full potential of any connection requires a system-level investigation, whereby the effect of the local behavior of the connection on the global response of the structural system is considered. Moreover, the connection should be tested under realistic load and boundary conditions and/or analyzed using an accurate yet computationally affordable analytical model. This paper represents a new system-level hybrid simulation application aimed at investigating the seismic performance of semirigid partial-strength steel frames with top and seat angles with double web-angle connections. The analytical component of the simulation comprises a detailed two-dimensional nonlinear FE model. The experimental component of the simulation consists of a full-scale beam-column subassembly with loading and boundary conditions that are in full interaction with the rest of the frame. The paper provides an overview of the hybrid simulation application and highlights the major results. The simulations were conducted at the Multi-Axial Full-Scale Sub-Structured Testing and Simulation Facility at the University of Illinois, which is part of the National Science Foundation Network for Earthquake Engineering Simulation.
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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) | 0.000 | 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 | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".