Numerical and experimental studies of the natural mixing behavior between an uncemented paste backfill and dumped waste rock in stopes from laboratory toward field conditions. Part I: Calibration and validation of a numerical model
Bibliographic record
Abstract
Underground mining operations generate large volumes of waste rock (W R ). Transporting this material to the surface requires significant energy and incurs operational costs. As an alternative, W R can be directly dumped into stopes being filled with cemented paste backfill (CPB), reducing both costs and greenhouse gas emissions. However, inadequate dumping may lead to poor mixing between cohesionless W R and CPB, resulting in fill mass collapse during or after adjacent stope excavation. Understanding and quantifying the natural mixing between dumped W R and CPB is therefore critical; yet, such studies are scarce. A major challenge lies in replicating large-scale field behavior through limited laboratory-scale tests using scalped (truncated) W R samples. Numerical modeling becomes essential to capture size effects related to both stope and W R particle sizes. In this study, a discrete element method (DEM)-based numerical model was employed. It was first calibrated using repose angle tests on W R samples with varying maximum particle sizes ( d max ), prepared using the scalping-down technique. All model parameters were determined through direct measurements, except for the rolling resistance coefficient ( µ r ) between W R particles, which should be obtained through numerical calibration. Initially, it was assumed that the µ r would vary with d max , in line with the observed increase in repose angle with larger d max . Surprisingly, calibration showed that µ r was not very sensitive to changes in d max , contradicting the experimental trend. Further investigation revealed that repose angle measurements are influenced by the quantity of material used; when sufficient W R mass is employed, the repose angle also becomes independent of d max . This confirms that scalped samples can reliably represent in situ W R in repose angle tests. The scalping technique is thus validated for use in laboratory piles tests. The predictive capability of the calibrated model is further supported by strong agreement with additional experimental data. This calibrated and validated numerical DEM model can now be confidently applied to analyze the mechanical behavior of W R -based infrastructures across varying particle sizes and field conditions. Its application to simulate the natural mixing between dumped W R and uncemented paste backfill is presented in Part II of this companion study.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".