Design and Construction of Roller-Compacted Concrete Pavements for Container Terminals
Bibliographic record
Abstract
Roller Compacted Concrete (RCC) is a zero-slump concrete consisting of dense-graded aggregate and sand, cementitious materials, and water. Because it contains a relatively small amount of water, it cannot be placed by the same methods used for conventional (slump) concrete. For pavement applications, the concrete is usually placed with an asphalt paver, and densified by compacting with, a vibrating roller. The resulting pavement surface is not as smooth as slip-form concrete paving, so a common use of RCC is to construct pavements in industrial areas where traffic speeds are slower and there is a requirement for a tough, durable pavement. The low water-cement ratio (usually ranging from .30 to .40) provides for high strengths. Common design compressive strengths for pavements are in the range of 35 – 55 MPa (5,000 – 8,000 psi) in 28 days. The principal advantages of RCC are derived from the construction process. Construction costs are lower because there is less labor involved in placing the concrete (no formwork or finishing is required), and no reinforcing steel or dowels are used. With the low water-cement ratio there is less paste in the concrete matrix, so there is no bleed water and less shrinkage than in conventional concrete. The dominant role of aggregate in the concrete provides load transfer across control joints and cracks by using aggregate interlock, which eliminates the need for load transfer devices. The use of RCC as a material to construct pavements began in the 1970's in Canada. It was originally used by the logging industry to provide an all-weather platform for unloading logging trucks and storing and sorting logs. In the past 25 years it has gained acceptance as a strong and durable pavement material that can withstand heavy loads and severe climates with little required maintenance.
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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".