Mechanical and Microstructural Behavior of Cemented Paste Backfill Under Cyclic Loading
Bibliographic record
Abstract
Understanding the mechanical and physical behavior of aged CPB under cyclic loading is a significant area of research. Many parameters such as cementation (hydration) and the microstructure, which dictate the arrangement of particles and permeability, affect the mechanical features of cemented paste backfill (CPB). The impact of a wide range of external energy sources within the mining environment, such as cyclic loading resulting from long-term blasting, can significantly alter the applied stresses on the backfill mass. This paper aims to delve into this crucial area of research. A series of uniaxial cyclic tests were conducted on CPB, utilizing samples made from tailing materials sourced from a copper mine in South Australia. Different loading levels were applied at various curing times. All samples exhibited cyclic loading hardening behavior for cyclic loading levels between 80% and 93% of monotonic unconfined compressive strength (UCS), and a cyclic loading damage behavior was observed for 96% of UCS loading level for both 14- and 28-day curing periods. To further investigate these findings, scanning electron microscope analysis as well as sonic velocity tests were conducted for capturing microstructural changes in the samples before and after tests. These findings can be used to indicate a safe firing distance to a filled mass.
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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 | 0.000 |
| 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".