Assessment of Acoustic Emission and Triaxial Mechanical Properties of Rock-Cemented Tailings Matrix Composites
Bibliographic record
Abstract
Acoustic emission (AE) test is a powerful technique for examining the sounds of cracks growing, breaking, and other modes of damage in cementitious materials deforming under stress, such as rock-cemented tailings matrix composites (RCTMC). RCTMC, an engineered mixture of tailings, cement, rock, and water, is widely used to fulfill numerous important roles at underground mine sites as a construction material and a ground support tool. To study the mechanical strength and AE properties of RCTMC, compression testing was carried out using a triaxial compression test system (TAW-2000) and AE monitoring system (PCI-2), and the failure modes of samples were also examined. Results have shown that (1) the failure process of RCTMC samples can be divided into six main stages: compaction, linear elastic characteristic, crack growth, primary damage development, cemented tailings backfill withstand stress zone, and secondary damage development stage. CTB has the strengthening effect on mechanical strength of rock; (2) the AE process can be also divided into six main stages: the prepeak quiescence period, the elastic energy reserve period, the first destruction development AE area, the secondary energy reserve period, the second damage development stage, and the postpeak calm period; and (3) samples’ cumulative ring count is “stepped” distribution over time, and the ring count has entered the postpeak flat stage after many active periods. The process of RCTMC samples from tensile to shear failure mode is represented by numerical simulation. Finally, the obtained experimental results can offer a useful reference for the further study of the mechanism of the surrounding rock and cemented tailings backfill structure.
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 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".