Effect of Mixture Composition on Washout Resistance of Highly Flowable Underwater Concrete
Bibliographic record
Abstract
The underwater casting of relatively thin lifts of concrete in water requires the proportioning of highly flowable concrete that can resist water dilution and segregation and spread readily into place. An investigation was carried out to determine the effects of antiwashout admixture concentration, water-cementitious materials ratio, and binder composition on the washout resistance of highly flowable concrete. Two main types of antiwashout admixtures were used: 1) a powdered welan gum at concentrations of 0.07 and 0.15% (by mass of binder); and 2) a liquid-based cellulosic admixture with dosages up to 1.65 L/100 kg of binder. The water-cementitious materials ratios were set at 0.41 and 0.47, corresponding to high-quality underwater concrete. Four binder compositions were used: a standard Canadian Type 10 cement, the same cement with 10% silica fume replacement, the cement with 50% granulated blast-furnace slag replacement, and a ternary cement containing 6% silica fume and 20% Class F fly ash. The concentrations of anti-washout admixture have direct impact on washout resistance. For a given washout loss, greater slump flow consistency can be achieved with the increases in anti-washout admixture concentration and decreases in water-binder ratio. The washout mass loss can be reduced, for a given consistency
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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 | 0.001 |
| 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 | 0.001 | 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".