One-Way Shear in Wide Concrete Beams with Narrow Supports
Bibliographic record
Abstract
Wide reinforced concrete beams are frequently used as primary structural members in buildings or bridges, to support floor loads and to transfer forces from discontinuous walls or columns above. In these roles, these critical members may in turn be supported on walls extending across the full width of the beam, or on narrower columns. While punching shear capacity on a perimeter around the column must be checked in the latter case, design code provisions require that one-way shear capacity be assessed for a cross-section encompassing the full width of the beam for both the wall and column support configurations. There was concern that this full-width shear area approach may lead to poor predictions of one-way shear strength, due to local geometry influences at the wide-beam-to-narrow-column connection. An experimental program on 8 large-scale shear-critical reinforced concrete beams is presented, where the support or load width, relative to the member width, was a primary test variable. The results show that the one-way shear strength was moderately reduced as the support width to beam width ratio decreased. This influence occurred for members without shear reinforcement and for members with a moderate shear reinforcement ratio. A capacity reduction function was developed to account for this influence on one-way shear strength, and its application demonstrated with a design example.
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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 | 0.000 | 0.001 |
| 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".