Investigation on uniaxial compressive strength of flocculated slurry backfill materials for minefill applications
Bibliographic record
Abstract
The purposes with regard to all underground voids filled with tailings are categorized into three aspects such as improvement safety issues(i.e.ground control),increasing economics(i.e.enhancing ore recovery rate),and environmental requirements(i.e.reduction acid water drainage).The types of backfill technologies include slurry backfill,paste fill and rockfill.The first two types of the backfill are also called as hydro-backfill,and rockfill is called as dried-backfill;all of which are applied to Canadian mines.UCS(uniaxial compressive strength) and permeability are critical parameters for slurry backfill in minefill applications,which affect on the quality of underground minefill.On the one hand,cement needs to be added into the slurry backfill materials to improve the strength of the fill materials;the huge tonnages of which are used for minefill and cement takes up the large component of mine fill costs;on the other hand,the coarse solid recovery used for backfill materials is classified from underflow of hydrocyclones,meanwhile fine parts flow out through overflow of the hydrocyclones to the tailings pool;sometime the backfill tailings of the mines are deficit and sand needs to be bought,which is mixed up with the tailings to be filled into the voids of underground.It is the concernful research issues for mine industry how to reduce the amount of cement added into backfill materials and improve the solid recovery particularly fine parts from underflow of the hydrocyclones in order to save the backfill costs.The effects of flocculant-assistance on UCS of tailings for slurry backfill are investigated.The results of the experiments indicate that the strength of tailings could be improved largely by the flocculant-assistance;moreover,the maximum strengths of backfill with flocculant-assistance are achieved at the optimization value of flocculant dosage,whereas the over-dosage of flocculant could have an adverse effect.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".