Review of nonlinear modelling parameters and acceptance criteria in ASCE 41 for seismic evaluation and upgrading of steel structures in Canada
Bibliographic record
Abstract
The seismic resilience of structures can be quantified through rigorous seismic assessment. Because no detailed guideline is available for nonlinear modelling parameters and the corresponding acceptance criteria for the seismic evaluation and upgrading of steel structures in Canada, the structural commentary of the National Building Code of Canada suggests using ASCE 41, which has been adopted as a standard for seismic evaluation and retrofit of buildings in the United States (U.S.). However, because the steel design standards in Canada and the U.S. are different, their applicability to steel structures in Canada needs to be investigated. To this end, this paper critically reviews the nonlinear modelling parameters and acceptance criteria, and then recommends whether these values need to be revised or are adopted as is for the seismic evaluation and upgrading of steel structures in Canada. A numerical example of a steel moment-resisting frame is presented to demonstrate the recommended parameters being used for seismic evaluation.
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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 | 0.022 | 0.039 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.012 | 0.010 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".