A simple method for determining seismic demands on gravity load frames
Bibliographic record
Abstract
This paper presents a simple method based on modal response spectrum analysis to compute internal forces in structural elements belonging to gravity framing not part of the seismic force resisting system (SFRS). It is required that demands on these gravity load resisting system (GLRS) be determined according to the design displacement profile of the SFRS. The proposed new method uses the fact that if the linear stiffness properties of the GLRS not part of the SFRS have negligible values compared to those of the SFRS, only the latter will provide lateral resistance. Displacements of the GLRS then correspond to those of the SFRS alone. The new method is illustrated by computing the seismic responses of a symmetric and an asymmetric multi-storey reinforced concrete building. These results are compared to those obtained from the application of the simplified analysis method proposed in the Canadian standard for the design of concrete structures. Nonlinear time history analyses are also performed to provide a benchmark for comparison. Results show that the new method can predict shear and bending moment in all members at once with ease. Therefore, this new simplified method can effectively be used to predict seismic forces in elements not considered part of the SFRS.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".