Experimental Study of Uniaxial Compressive Strength (UCS) Distribution of Hydraulic Backfill Associated with Segregation
Bibliographic record
Abstract
Stope backfilling with mine wastes has become a common practice in underground mines worldwide. Despite the increasing popularity in paste and rock fills, hydraulic fill made of classified mill tailings or sands remains commonly used in many mines. When such a slurried material is placed in a mine stope, a phenomenon known as segregation can take place associated with the quick drainage and consolidation of the hydraulic fill, thereby leading to a heterogeneous fill mass. While numerous publications have focused on the alleviation of segregation, there are few studies on the characterization of the distribution of geotechnical properties within hydraulic fill due to segregation. It is particularly scarce to quantify the spatial variation of the segregation and the resulting geotechnical properties after a backfill is placed in an opening. There is also a gap to quantitatively describe the degree of segregation using an appropriate expression or definition. The aim of this study is to investigate the effect of the segregation on the spatial variation of the geotechnical properties of hydraulic fill. Laboratory tests were performed with the cemented hydraulic backfill prepared with columns of different heights. The experimental results indicate that the segregation takes place and the resulting physical and mechanical properties can vary throughout the columns for samples higher than twice of the standard size. These results also indicate that the mechanical properties of a hydraulic fill obtained in a laboratory following the current practice with standard samples may not be representative of the fill mass placed in mine stopes. Expressions are proposed to quantify the degree of segregation associated with the spatial variation of particle sizes of mine hydraulic backfill.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".