Impact of balcony geometry on the performance of rubberized concrete structures against progressive collapse
Bibliographic record
Abstract
Purpose Evaluate the performance of progressive collapse of full-scale three-dimensional structure (3D) beam-slab substructures with and without the presence of reinforced concrete (RC) balconies using two concrete mixes [normal concrete (NC) and rubberized concrete (RuC)]. Design/methodology/approach This study examines two concrete mixes to evaluate the progressive collapse performance of full-scale 3D beam-slab substructures with and without the presence of RC balconies using the finite element (FE) method. Findings The results showed that the vertical loads that affect the structures of the specimens after including the balconies in the modeling increased by an average of 29.3% compared with those of the specimens without balconies. The specimens with balconies exhibited higher resistance to progressive collapse in comparison with the specimens without balconies. Moreover, the RuC specimens performed very efficiently during the catenary stage, which significantly enhanced robustness to substantial deformation to delay or mitigate the progressive collapse risk. Originality/value All the experimental and numerical studies of the RC beam-slab substructures under progressive collapse scenarios are limited and do not consider the balcony’s presence in the building. Although balconies represent a common feature of multistory residential buildings, their presence in the building has more likely caused the failure of this building compared with a building without balconies. However, balconies are an external extension of RC slabs, which can provide extra resistance through tensile membrane action (TMA) or compressive membrane action (CMA). All those gaps have not been investigated yet.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".