Nonlinear Seismic Analysis of Steel Concrete Composite Structures
Bibliographic record
Abstract
Reinforced concrete (R.C.) buildings are highly vulnerable to seismic failures due to soft story mechanisms and low ductility. Steel-concrete composite frames offer improved ductility, lateral load resistance, and energy absorption under seismic forces. This study investigates the seismic performance of steel-concrete composite buildings with and without masonry infill walls using a probabilistic fragility-based approach. A fifteen-story composite frame is analyzed in bare and infill configurations through non-linear static pushover analysis, and fragility curves are developed to assess damage probabilities at various performance levels.The results demonstrate that composite infill frames significantly improve lateral stiffness, base shear capacity, and seismic resilience compared to bare frames. Incorporating masonry infill substantially reduces the probability of failure across all damage states. Additionally, seismic performance assessments of low-rise, mid-rise, and high-rise composite buildings using Incremental Dynamic Analysis (IDA) reveal that low-rise structures exhibit reduced dispersion and more predictable seismic responses.This research highlights the effectiveness of masonry infill and composite construction in enhancing seismic safety and provides a valuable framework for performance-based seismic design in earthquake-prone regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".