Estimating Limit State Capacities for OGS Building having different Multiplication Factor
Bibliographic record
Abstract
Seismic fragility curves are one of the famous methods to address the problem of performance of building in probabilistic approaches.It considers the uncertainties in load and demand; it gives reliable results to take decisions.In seismic fragility analysis, curves for different structural performance levels are plotted against the structural demand.The structural capacities or structural limit state (LS) capacities is of crucial importance.LS capacities are elaborated in design codes and several research has done to estimate the LS capacities using Push over analysis.However, there is an uncertainty in the building due to the presence of infill walls as well; infill walls add additional stiffness against lateral loads.And in the case of Open Ground Storey (OGS), the complexity is added to one more level due to the absence of infill walls in ground storey.International codebooks suggest to use magnification factor (MF) in ground storey to have good performance under lateral loads for OGS building.The present study focuses on evaluating the LS capacities for buildings of two storey and four storey buildings with different scheme of MF.The results shows that there is a wide disparity in storey wise LS capacities.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".