Shear resistance of self-consolidating concrete beams — experimental investigations
Bibliographic record
Abstract
Self-consolidating concrete (SCC) is a new generation of high performance concrete known for its excellent deformability and high resistance to segregation and bleeding. Lack of information regarding in situ properties and structural performance of SCC is one of the main barriers to its acceptance in the construction industry. There is some concern among researchers and designers that SCC may not be strong enough in shear because of some uncertainties in mechanisms resisting shear — notably the aggregate interlock mechanism. Because of the presence of comparatively smaller amount of coarse aggregates in SCC, the fracture planes are relatively smooth as compared with normal concrete (NC) that may reduce the shear resistance of concrete by reducing the aggregate interlock between the fracture surfaces. The paper compares the shear resistance of SCC and NC based on the results of an experimental investigation on 18 flexurally reinforced beams without shear reinforcements. The test parameters include concrete type, maximum size of coarse aggregate, coarse aggregate content, and beam shear span-to-depth ratio. Shear strength, shear ductility, crack patterns, and failure modes of all experimental beams are compared to analyze the shear resistance mechanisms of SCC and NC beams in both pre- and post-cracking stages. The recommendations of this paper can be of special interest to designers considering the use of SCC in structural applications.Key words: self-consolidating concrete, shear resistance, shear resistance factor, aggregate interlock, dowel action.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".