Consolidation and mechanical response of cemented tailings backfill to multiaxial stresses from rockwall closure and self-loading
Bibliographic record
Abstract
Cemented paste backfill (CPB) is a key material in underground mining, providing essential ground support while aiding in tailings management. However, current research has overlooked the combined effects of horizontal rockwall closure stress and vertical self-loading stress, referred to as multiaxial stress, on the CPB’s consolidation behavior and its mechanical properties development. Understanding and assessing these effects is critical because they directly affect the stability and performance of CPB structures. In this study, a novel multiaxial compressive stress curing and monitoring apparatus was used to simulate two horizontal rockwall closure scenarios with a consistent backfilling rate, under both drained and undrained conditions. Key parameters assessed included unconfined compressive strength (UCS), deformation during curing, stress-strain behavior, and modulus of elasticity. The results highlight that rockwall closure, combined with vertical stress, plays a pivotal role in the consolidation behavior of CPB, significantly affecting key mechanical properties. Higher horizontal stress from faster rockwall closure intensified compression during curing, leading to reduced porosity, enhanced particle rearrangement, and accelerated consolidation. This intensified consolidation leads to notable improvements in mechanical properties, including increased UCS, enhanced stiffness, and a higher modulus of elasticity, indicating improved load-bearing capacity. Moreover, the interaction between multiaxial stress and drainage conditions influenced stress-strain behavior and deformation, with drained conditions promoting earlier plasticity and higher peak stresses. These findings underscore the critical influence of multiaxial stress, combined with drainage conditions, on CPB performance, offering valuable insights for optimizing CPB design in underground mining applications.
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".