Behavior of high-performance RC composite corbels with inclined stirrups
Bibliographic record
Abstract
In the present work, a new modified arrangement for shear reinforcement in corbels is proposed. Inclined, rather than horizontal, alignment of stirrups was studied. In addition, the performance of composite corbels incorporated with the usual and proposed alignments of the shear reinforcement were investigated. The experimental work consisted of testing 12 specimens. Four corbels are non-composite and eight are composite with two shapes of rolled steel, namely, WF and tapered WT sections. Two values of shear span to depth ratio (av/d) have been considered, which are 0.70 and 1.0, to study both when shear is dominant and when bending moment is dominant. The behavior of the tested specimens was discussed in terms of the history of loading, first cracking load, failure load, ductility, toughness, and history of the first crack development. It was found that the proposed configuration of shear reinforcement improved the ductility and toughness with respect to the conventional arrangement by 16% and 38%, respectively, for av/d value of 0.70, and 55% and 64%, respectively, for an av/d value of 1.0. Furthermore, the results revealed that using the composite corbel with the proposed alignment rather than RC corbel improved the ductility and toughness by 35%–80% and 45%–173%, respectively, for av/d = 0.70. The values for corbels with av/d = 1.0 are 38%–101% and 67%–88%, respectively. Moreover, tests revealed that the composite WF-steel corbel with diagonally aligned stirrups showed relative performance indicators (with respect to the conventional corbel) for av/d = 0.7 of 82%, 98%, 105%, and 273% for the first cracking load, failure load, ductility, and toughness, respectively. The respective values for av/d = 1.0 were 111%, 115%, 138%, and 188%, respectively.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".