Simulation of cemented paste backfill (CPB) deposition through column experiments: comparisons of field measurements, laboratory measurements, and analytical solutions
Bibliographic record
Abstract
Estimating the as-placed properties of mine backfill is fundamental to optimizing the safety and productivity of underground mines. For cemented paste backfill (CPB), an important consideration is the extent to which self-weight consolidation during deposition may reduce the void ratio and enhance the binder’s effectiveness. Field monitoring and sampling campaigns can help investigate this phenomenon but they are expensive and logistically difficult. Therefore, mesoscale column experiments are performed in the controlled laboratory environment to better understand the coupling between self-weight consolidation and cement hydration. In this paper, columns are backfilled with uncemented paste tailings and with CPB and the pore water pressure, electrical conductivity, and volume changes are monitored during and after backfilling. The pore water pressure profiles at the end of backfilling are compared with an available analytical solution and restrictions on the solution’s validity are identified. Void ratios of samples taken from columns are compared with the ones obtained from field samples and the similarity indicates the filling conditions simulated in the laboratory are representative of field conditions. The changes in void ratio after curing were small compared to the initial void ratio of fresh CPB. The tests’ results help explain why self-weight consolidation during backfilling is not significant at the studied mine, which may be the case for many other mining operations as well.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".