Performance of aggregate sizes on crack bridging and capacity enhancement of deep beams
Bibliographic record
Abstract
Reinforced concrete deep beams (RCDBs) investigations are often complex because of the highly disturbed zones which may aggravate the shear performance under variable loadings. The shear capacity enhancement of RCDB using different aggregate sizes of 19 mm, 25 mm, and 50 mm has been investigated under three-point monotonic loading. Nine RCDBs with 750 × 170 × 225 mm dimensions were considered, and the beam was loaded at a 1.4 shear span to depth ratio. Three of the beams were designed without web reinforcement, and six were designed for web reinforcement with varied aggregate sizes. There was no significant difference in the shear strength of RCDBs considered however, a 50 mm aggregate beam was found capable of reducing the multiple crack propagations when compared to other aggregate-size beams. Additionally, the shear reinforcement increased the ductility and strength by over 30% and 20%, respectively. The applicability of 3-dimensional FEM extended to the investigation acceded with the shear response of the experiment exercising shear stiffening behavior. The estimated model from the modified ACI 318:05 can predict the shear capacity of the RCDB with higher accuracy. Since aggregate resists the load by aggregate interlock action, it is crucial to choose the right aggregate when building concrete structural components. The results of this study will help engineers choose the best aggregate for a certain structural element.
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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 | 0.000 | 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) | 0.000 | 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".