Pore Water Pressure Variations in Cemented Paste Backfilled Stopes
Bibliographic record
Abstract
Cemented paste backfill (CPB) has gained popularity over the past decade over other mine waste management techniques due to its high delivery rate and tight characteristics. CPB is a mixture of mine tailings, water and binder (cement). CPB has both environmental and operational benefits to a mine. Fresh CPB is being held in the stope by means of a barricade until it is cured and is self-supportive while mining operations such as blasting are going on. Barricade safety is crucial as the barricade failure would cause injuries and casualties to mining personnel as well as adding additional costs. The pressure acting on the barricade is dependent on the pore pressure that is developed and dissipated in and from CPB. The problem of self-weight consolidation of an accreting material was first studied by Gibson (1958). Shahsavari and Grabinsky (2015) modified the Gibson solution based on a new boundary condition that was inferred from in-situ measurements. However, Shahsavari and Grabinsky (2015) ignored the effect of hydration on pore pressure variations. In this study, a 1D analysis using FLAC3D is performed where the effect of hydration on pore pressure is considered through the change in material properties with time. The time dependent coefficient of permeability and shear modulus are then used to predict the pore pressure variations with time.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 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".