In situ behaviour of cemented hydraulic and paste backfills and the use of instrumentation in optimising efficiency
Bibliographic record
Abstract
Better understanding of in situ backfill behaviour can allow mines to optimise backfilling efficiency. To this end, a significant quantity of fieldwork has recently been conducted by University of Toronto (U of T) and Mine Design Engineering (MDEng.), focused on in situ measurements in cemented paste backfill. Using these ‘production friendly’ instrumentation approaches, new fieldwork data from two of Vale’s Canadian operations are presented, to demonstrate how instrumentation can be applied to better define the behaviour of cemented hydraulic backfills. Instrumentation consists of clusters of total earth pressure cells, piezometers (for pore pressure) and thermistors that are placed remotely in open stopes, and mounted on barricades. Backfilling with cemented hydraulic fill requires consideration of drainage and potential segregation affects, which are not associated with paste. In situ data demonstrates the transition of the backfill from a fluid to soil-like material at various locations in backfilling stopes. Within a relatively coarse grained (i.e. sand) cemented hydraulic fill, this transition occurred relatively quickly (after three hours). For a sand and tailings blend of cemented hydraulic fill however, the hydrostatic loading condition persisted for between 12 and 24 hours. During backfilling, this information, combined with barricade pressure data, was used to optimise requirements for the post-plug cure period, saving up to three days of stope cycle time. The measurements in hydraulic fill are contrasted with previous fieldwork data from cemented paste backfill. Strength gain mechanics differ between the fill types, through the requirement for drainage in hydraulic fills, whereas cement content and self-desiccation mechanisms appear to dominate in situ measurements in paste. Hydraulic fills exhibit particle size segregation which results in spatial variation in cement content, and so spatially distinct pressure and temperature responses for the interpreted coarse and fine grain zones were measured. A measured low temperature zone was interpreted to represent a coarse grain size fill with an at rest earth pressure coefficient similar to that of a dense sand. A high temperature zone was interpreted to represent a fine grain size fill which features higher cement content. The significantly greater temperature measured in the binder-rich areas are thought to induce ‘thermal expansion’ generated pressure increases. This work demonstrates the potential for instrumentation to feature as part of a considered quality control policy (that includes barricade construction and drainage checks) to safely optimise backfilling efficiency.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".