Performance-Based Specifications of Workability Characteristics of Prestressed, Precast Self-Consolidating Concrete—A North American Prospective
Bibliographic record
Abstract
Adequate selection of material constituents and test methods are necessary for workability specifications and performance of hardened concrete. An experimental program was performed to evaluate the suitability of various test methods for workability assessment and to propose performance specifications of prestressed concrete. In total, 33 self-consolidating concrete (SCC) mixtures made with various mixture proportioning parameters, including maximum size and type of aggregate, type and content of binder, and w/cm were evaluated. Correlations among various test results used in evaluating the workability responses are established. It is recommended that SCC should have slump flow values of 635-760 mm. To ensure proper filling capacity greater than 80%, such concrete should have a passing ability that corresponds to L-box blocking ratio (h₂/h₁) ≥ 0.5, J-Ring flow of 570-685 mm, slump flow minus J-Ring flow diameter ≤75 mm. Moreover, Stable SCC should develop a column segregation index lower than 5%, and rate of settlement at 30 min of 0.27%/h for SCC proportioned with 12.5 or 9.5 mm MSA. It is recommended that SCC should have a plastic viscosity of 100-225 Pa·s and 100-400 Pa·s for concrete made with crushed aggregate and gravel, respectively, to ensure proper workability.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".