Strength and Deformation Characteristics of Electric Arc Furnace Slag as Ballast Aggregate
Bibliographic record
Abstract
The accumulation of waste by-products, such as steel slag, has become a significant environmental concern in waste management.In recent years, the reuse of waste materials in structural fills and pavement subbase materials has increased as part of efforts to promote sustainable waste recycling.On this basis evaluating potential alternative for railway ballast materials is valuable, particularly from the prospective of mechanical performance.This study examines the potential of EAF slag as a railway ballast material through a comprehensive series of laboratory tests, including physical and mechanical evaluations.Monotonic and cyclic triaxial tests are performed to evaluate its shear strength and permanent deformation characteristics under field representative stress condition.The performance of EAF slag is subsequently compared with various ballast materials reported in the literature.The results indicate that the EAF slag meets the standards established by major countries.Additionally, its performance aligns with previously published data for natural aggregate ballast materials, demonstrating promising shear strength, less permanent deformation, and improved stiffness under repeated loading.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".