Estimating the Higher-Mode Response of Ductile Structures
Bibliographic record
Abstract
While the importance of higher-mode actions is appreciated within the engineering community, the affect that ductile nonlinear response has on higher-mode characteristics and the subsequent implications this has for design has received little attention. In this article, the manner in which the higher-mode response of frame-wall structures is affected by inelastic behavior is closely examined and a means of accounting for this in design is proposed. The work focuses firstly on the characteristics of the higher modes present at the development of peak response and then considers how these characteristics would affect the total forces in the building. The study utilizes a series of nonlinear time-history analyses of two different groups of RC frame-wall structures subject to a suite of real records. It is shown that a new modal analysis approach that incorporates transitory inelastic modal characteristics gives significantly improved predictions of peak base shear in frame-wall structures than more traditional modal analysis methods which use elastic higher-mode characteristics. The issues associated with the use of transitory inelastic modal characteristics are discussed and various challenges that would need addressing for the prediction of other response parameters and structural types are identified.
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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".