Experimental Study on Direct Tensile Properties of Cemented Paste Backfill
Bibliographic record
Abstract
Cemented paste backfill (CPB) has been increasingly utilized in mines for efficient mineral obtaining and regional ground support. To guarantee the work performance, the mechanical properties of CPB have long been a topic of study among researchers. But the research progress on the tensile strength of CPB is limited, mainly because of the lack of an appropriate test method due to the low tensile strength of CPB. Therefore, instead of the conventional splitting indirect tensile strength test method, a new direct tension test method, which utilizes the specifically designed compression to tension load converter (CTLC) and dog-bone-shaped specimen, has been applied to study the direct tensile properties of CPB. In this study, the direct tensile strength (DTS) of 47 CPB mix designs were measured using CTLC, and the unconfined compressive strength (UCS) of the corresponding mix design was also tested. The experimental results showed that the increase in the binder content, solid mass content, and curing period led to higher CPB direct tensile strength, and the DTS of CPB was most sensitive to the binder content. Furthermore, the influence of the slurry mass solid content on the tensile strength of CPB was not linear. The influence of the binder content became increasingly notable with the increase in the solid content, especially if the binder content exceeded 75%. The effect of the curing period was found to be rather marginal due to the decreasing amount of un-hydrated cementitious materials left with the increase of the curing period. Overall, the DTS generated using dog-bone specimens and the CTLC apparatus are valid for better mine backfill designs. Finally, a linear correlative between UCS and DTS with a formula in the form of σDT (DTS) = 0.171 σc (UCS) was obtained, and the correlation was sufficient for further calculation of DTS using measured UCS.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".