The Over-Strength Coefficient of Masonry-Infilled RC Frame Structures under Bidirectional Ground Motions
Bibliographic record
Abstract
The over-strength coefficient is one of the key factors for the seismic safety of a structure. For RC frames, the infill wall may improve the lateral bearing capacity, while the seismic demand increases as well, which leads to the unexpected seismic performance of an infilled RC frame in past earthquakes. Therefore, it is necessary to systematically study the over-strength effect of the infilled RC frames from the point of seismic capacity and demand. In this paper, 36 RC frame structures with/without infill walls are designed, and the corresponding finite element modelings, considering the in-plane and out-of-plane performance coupling effect of infill walls, are established to conduct incremental dynamic analyses (IDA). The seismic capacity values of over-strength coefficients are calculated, utilizing the IDA results under bidirectional ground motions. The effects of seismic precautionary intensity and number of stories on the over-strength coefficient of the RC frame with/without infill walls are discussed. The over-strength coefficient capacity value of the infilled frame is apparently higher than that of the bare frame, due to the contribution of infill walls. However, the seismic demand analysis of the over-strength coefficient shows that the capacity–demand ratio of masonry-infilled RC frame structures is greatly reduced, especially for the bottom soft-story infilled frame.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".