Structural system yielding minimum differences between ordinary and staged analyses
Bibliographic record
Abstract
Abstract Structural engineers should appropriately design concrete structures to resist lateral loads. Determining the adequate system for resisting the expected lateral loads is important to control the building drift. Choosing the appropriate system is usually conducted assuming the predicted forces are applied to completed concrete buildings at one step which is commonly known as ordinary analysis (OA). Nevertheless, these structures are constructed sequentially which requires using staged analysis (SA) instead of OA. In this paper, a comprehensive numerical model for SA of concrete buildings, which accounts for time dependent effects, is utilized using a well-validated commercial software. Six reinforced concrete buildings with 10 and 20 storeys are analyzed using the developed model. Three various structural systems are considered (Rigid Frame (RF), Shear Wall (SW), and Wall Frame (WF). A comparison is conducted between the displacements and internal forces in beams and slabs obtained from the SA and OA. For a 10-storeys RF building, maximum bending moment from SA is 29.9% higher than that from OA. The same conclusion was observed for the maximum shearing force with a percentage of 19.6%. Moreover, maximum bending moments and shearing forces from SA for the 20-storeys RF building are, respectively, 35.0% and 23.5% larger than those from OA. The RF and WF systems provided the minimum difference in differential displacement between the OA and SA analyses. The RF system produced the least differences in internal forces from OA and SA for all studied buildings.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".