Understanding the Triaxial Behavior of Cemented Tailings Backfill Reinforced with Fibers
Bibliographic record
Abstract
Fiber-reinforced cemented paste backfill (FRB), a composite material incorporating fibers and cement into mine tailings, is extensively utilized in mine backfilling to ensure underground excavation stability. The triaxial mechanical properties and behavior of FRB, however, are not fully validated. This study investigates FRB specimens with varying fiber (1%, 2%, and 3%) and cement (3.0%, 4.5%, and 6.0%) contents, cured at room temperature. Consolidated drained (CD) and consolidated undrained (CU) triaxial tests were conducted on specimens cured for up to 28 days. The results show that axial strain–stress behavior transitioned from strain-softening to strain-hardening with increased curing time, fiber content, cement content, and confining pressure. The shear strength parameters determined using the Mohr–Coulomb criterion were consistent across CD and CU tests. Notably, 15% deviatoric stress and cohesion increased with fiber content and curing time, while the friction angle remained largely unaffected. Volumetric strain and pore-water pressure evolution revealed an initial contractive phase, followed by dilation in all specimens, highlighting the dependence of stress–dilatancy behavior on curing time and fiber content. Other key observations include the induction of stronger bonds by FRB hydration products and a shift from CPB softening to hardening patterns, underscoring significant advancements from prior studies. These findings enhance the understanding of FRB’s triaxial behavior and contribute to designing safer, cost-effective FRB structures for underground support.
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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 | 0.000 | 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) | 0.001 | 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".