Roof Movement and Failure Behavior When Mining Extra‐Thick Coal Seams Using Upward Slicing Longwall‐Roadway Cemented Backfill Technology
Bibliographic record
Abstract
A novel and environmental‐friendly backfill mining method known as upward slicing longwall‐roadway cemented backfill (USLCB) technology has recently been proposed and successfully applied in mines extracting extra‐thick coal seams located under sensitive areas. This paper studies the effects USLCB had on roof movement and failure behavior using the mechanical analysis approach. The application of USLCB in the Gonggeyingzi Mine is taken as a case study with roof movement behavior being monitored over a single mining cycle, as well as over multiple mining cycles of different coal slices. In addition, backfill performance requirements to prevent roof failures where USLCB is implemented are studied. The results show that the deflection curves of the roof at the end of each mining cycle during mining the first and the six slices are symmetrical, but they change from asymmetrical to symmetrical during the mining progresses of the second slice to the fifth slice. The final state of roof movement after the first slice, and through to the fifth slice, displays an obvious “flat bottom” pattern in the middle of the deflection curve. The roof movement during the removal of the top slice is noticeably different from other slices. The results also show that the requirements of the elastic modulus, as well as the strength of the backfill, increase as the number of mined slices increases from 1 to 5, but the requirements drop sharply for mining the top slice.
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 | 0.000 | 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".