Effect of Mixture Composition on Relative Strength of Highly Flowable Underwater Concrete
Bibliographic record
Abstract
Concrete used for underwater repair is often proportioned to spread readily into place and self-consolidate, and to develop high resistance to segregation and water dilution. An investigation was carried out to determine the effect of the dosage of antiwashout admixture, water-cementitious materials ratio (w/cm), and binder composition on the relative residual strength of highly flowable underwater concrete. Two types of antiwashout admixtures were used: a powdered welan gum at 0.07 and 0.15% by mass of binder, and a liquid-based cellulosic admixture employed at a high dosage of 1 to 1.65 L/100 kg of cementitious materials. The w/cms were set at 0.41 and 0.47 to secure adequate performance of underwater concrete for construction and repair. Four binder compositions were used: a Canadian Type 10 cement; a cement with 10% silica fume replacement; a cement with 50% replacement of granulated blast-furnace slag; and a ternary binder containing 6% silica fume and 20% Class F fly ash. Test results indicate that for a given washout mass loss and slump flow consistency, greater relative residual strength can be secured when the dosage of antiwashout admixture is increased, the w/cm is reduced, and a binary binder with 10% silica fume substitution or the ternary binder are employed. Such mixtures can develop relative residual compressive strengths of 85 and 80%, compared to mixtures cast in air, when the value of washout loss is limited to 4 and 6% for mixtures with slump flow values of 450 and 550 mm, respectively.
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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 | 0.002 |
| 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 | 0.001 |
| 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".