Sustainable Reuse of Coal Mine Waste: Experimental and Economic Assessments for Embankments and Pavement Layer Applications in Morocco
Bibliographic record
Abstract
This paper deals with the potential reuse of coal mine waste rocks (CMWR) as an alternative material for road construction to conserve the natural resources and sustainable management of mining waste. The investigation was conducted through the determination of the chemical, mineralogical, geotechnical properties, and acid mine drainage formulation of CMWR as well as economic feasibility. This waste was used either alone for embankments and mixed with stabilizing agents fly ash (FA) and hydraulic road binder (HRB) for pavement applications. The experimental results confirmed that weathered CMWR can be successfully used alone as a sustainable alternative material for the embankment. Furthermore, the use of stabilizing agents in the following ratio CMWR:FA:HRB = 80:20:5 allow the use of CMWR in road sub-base layers for high-traffic pavements. Also, the environmental investigations showed that CMWR does not present any potential contaminating risk on the surrounding environment and most of the pyrite particles were already oxidized. Therefore, the environmental impact of acid mine drainage produced by pyritic waste throughout its life cycle can be neglected. Finally, an economic case study confirmed the workability of CMWR reuse in a radius of 29 km around their dumps by resulting in a lower cost compared with conventional materials.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".