A General Review on Longwall Mining-Induced Fractures in Near-Face Regions
Bibliographic record
Abstract
It is believed that underground longwall mining usually produces fractures in the surrounding rocks. On the one hand, mining-induced fractures not only degrade the strength of the rock mass but also serve as main channels for fluids (e.g., water and methane). Fractures facilitate the failure of the rock mass and fluid inrush into working spaces. Therefore, mining-induced fractures are significant for the safety evaluation of underground structures and finding feasible solutions. On the other hand, the fractures are also beneficial for methane collection and coal fragmentation, which are essential for the successful operation of longwall top coal caving mining. Therefore, determining the characteristics of induced fractures is significant for underground longwall mining. From a global perspective, longwall mining-induced fractures in the overburden have been well studied, which improves the understanding of the mining pressure and ground control. However, induced fractures near the longwall face, which have more significant effects on mining activities, have not been summarized. The goal of this review paper is to provide a general summary of the current achievements in characterizing mining-induced fractures in near-face regions. The characteristics of mining-induced fractures in the coal wall, chain pillar, immediate roofs and top coal, and floors are reviewed and summarized. Remarks are made on the current progress of, fundamental problems with, and developments in methodologies for characterizing mining-induced fractures using methods such as field observations, small-scale laboratory tests, physical modeling, and numerical modeling. Based on a comprehensive analysis, the advantages and disadvantages of each method are discussed, and the ideal conditions for applying each of these methods are also recommended.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".