Specific Mixing Energy of Cemented Paste Backfill, Part II: Influence on the Rheological and Mechanical Properties and Practical Applications
Bibliographic record
Abstract
The rheological properties (yield stress, flow index and infinite dynamic viscosity) and mechanical properties (unconfined compressive strength, UCS) of different cemented paste backfill (CPB) recipes must be determined during the laboratory optimization phase. However, the influence of the mixing procedure on these properties has scarcely been studied so far. The objective of this paper is to assess to what extent these properties depend on the specific mixing energy (SME) for a given type of mixer. CPB recipes were prepared based on two types of tailing (CPB-T1 and CPB-T2, also referred to as T1 and T2) at a fixed solid percentage for each type of tailing using the Omcan laboratory mixer. A mixture of 80% slag and 20% GU was used as a binder. The mixing time and the rotation speed of the mixer were successively varied. For each recipe prepared, we determined the SME, the rheological properties of fresh CPB (at the end of mixing) and the UCS at 7, 28 and 90 days of curing. The results show that yield stress and infinite viscosity decreased when SME increased in an interval going from 0.3 to 3.8 Wh/kg and 0.6 to 6 Wh/kg for CPB-T1 and CPB-T2, respectively. An increasing trend in UCS with increasing SME was also observed. Empirical equations describing the change of the rheological properties with the SME are used to estimate the change in rheological properties of CPB along the distribution system, considering the specific energy dissipation during CPB transportation. A mixing procedure for obtaining CPB mixtures that are representative of CPB deposited in underground mine stopes is suggested for laboratories who currently use a same mixing procedure, irrespective of the variable field specific energy.
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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 | 0.000 |
| 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".