Steel Slag Aggregate Used in Portland Cement Concrete
Bibliographic record
Abstract
The issue of sustainability in the built environment is increasingly important, particularly in the transportation sector. In some cases slags from the iron and steel industries can be used to replace natural aggregates in construction. In this research, laboratory investigations of the use of steel slag as a portland cement concrete (PCC) aggregate were reviewed. Much of this research took place outside the United States. Some limited field cases of the use of steel slag in pavements were found. In at least two cases dramatic pavement failure resulted, but it is not known whether the slag used in the applications had been properly aged as required by modern specifications. Research on the use of steel slag aggregate in PCC has been carried out in Spain, Germany, Canada, Italy, India, and Saudi Arabia. Despite some limited field applications, virtually all research has been done in the laboratory. Much of this work shows that properly aged steel slag can be nonexpansive when used in PCC. When these research results are evaluated, it is important to consider the properties of the slags used because they may differ from the slags produced in the United States due to differences in sources or industrial processes. Several state department of transportation specifications were reviewed, and they generally do not permit the use of steel slag as a PCC aggregate. Steel slag represents a small part of the total aggregates currently used, but it is an alternative material that should be considered where it makes economic sense.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".