Seismic ratcheting of eccentric gravity loaded moment‐resisting frame buildings
Bibliographic record
Abstract
Structures may predominantly inelastically deform in a single direction during earthquakes and incur greater damage. This behavior is known as seismic ratcheting and can be caused by eccentric gravity loads. Code clauses were introduced in Canada and New Zealand to amplify displacements obtained from static analysis methods to consider seismic ratcheting effects. However, such clauses are based on analyses of reinforced concrete (RC) wall or single-degree-of-freedom (SDOF) structures, and methods to mitigate seismic ratcheting behavior were not explicitly provided. In this study, parametric analyses of steel and RC moment resisting frame buildings were performed to evaluate the adequacy of code clauses, identify parameters which influence seismic ratcheting behavior, and propose methods to mitigate such behavior. It was found that the New Zealand code underestimated the displacement increase for RC buildings, though it was able to envelope the displacement increase for steel buildings while the Canadian code was conservative. Additionally, the displacement increase was found to be sensitive to the building’s post-yield behavior and ground motion properties. However, assumptions of these properties during design may not be reflective of the actual building and seismic conditions, indicating that a reliable estimate of the increase in displacement is difficult to obtain. Instead, employing mitigation measures to reduce seismic ratcheting effects, such as designing to higher seismic demands, adding a secondary structural system to increase the building’s post-elastic stiffness, or providing more balanced lateral strengths after adjusting for eccentric gravity load effects are better measures to counter seismic ratcheting effects caused by eccentric gravity loads.
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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 | 0.001 | 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) | 0.001 | 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".