A Displacement Based Design Approach For Seismic Assessment of Flat Slab Structure With Core Shear Wall
Bibliographic record
Abstract
Reinforced concrete (RC) structures containing flat slab system and core shear wall have become popular and have been used extensively all over the world for the last few decades.They provide substantial advantages over the traditional beam-column-slab structures in terms of architectural aesthetics, easier fixing of electrical, lift, and plumbing lines.Usually, the building system consists of an RC core shear wall and columns directly connected to the slabs.Though the design procedure is similar to the structural type consisting of moment frames, the existing force-based seismic design practice has some limitations in considering response modification factors, design overstrength, deflection amplification factors, ductility, etc.In this study, an 8-storey flat slab RC structure with core shear-wall and gravity columns is considered for non-linear dynamic analysis.The displacement-based design approach addressed six pairs of ground motions.The core wall was modelled as fiber hinge model where hysteretic responses of both concrete and steel fiber responses are investigated.The results are presented in terms of the storey response, base shear, and roof displacement of the structure.Column, wall, and fiber hinges responses highlight the states of individual components as well as the fibers.Finally, the stress and strain levels of concrete and steel fibers are examined to check the overall status of the structural system.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".