A Numerical Study of Stress Distribution and Fracture Development above a Protective Coal Seam in Longwall Mining
Bibliographic record
Abstract
Coal and gas outbursts are serious safety concerns in the Chinese coal industry. Mining of the upper or lower protective coal seams has been widely used to minimize this problem. This paper presents new findings from longwall mining-induced fractures, stress distribution changes in roof strata, strata movement and gas flow dynamics after the lower protective coal seam is extracted in a deep underground coal mine in Jincheng, China. Two Flac3D models with varying gob loading characteristics as a function of face advance were analyzed to assess the effect of gob behavior on stress relief in the protected coal seam. The gob behavior in the models is incorporated by applying variable force to the floor and roof behind the longwall face to simulate gob loading characteristics in the field. The influence of mining height on the stress-relief in protected coal seam is also incorporated. The stress relief coefficient and relief angle were introduced as two essential parameters to evaluate the stress relief effect in different regions of protected coal seam. The results showed that the rock mass above the protective coal seam can be divided into five zones in the horizontal direction, i.e. pre-mining zone, compression zone, expansion zone, recovery zone and re-compacted zone. The volume expansion or the dilation zone with high gas concentration is the best location to drill boreholes for gas drainage in both the protected coal seam and the protective coal seam. The research results are helpful to understand the gas flow mechanism around the coal seam and guide industry people to optimize borehole layouts in order to eliminate the coal and gas outburst hazard. The gas drainage programs are provided in the final section.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".