Simulation of Ground Stress Field and Advanced Prediction of Gas Outburst Risks in the Non-Mining Area of Xinjing Mine, China
Bibliographic record
Abstract
In order to predict in advance the coal and gas outburst risks in the No. 3 coal seam in the non-mining area of the Xinjing mine, the strata were divided into seven rock assemblage types based on the lithologic characteristics of strata in the research area, and eight geological profile models were constructed. The finite element methods were used to simulate the ground stress field of the No. 3 seam floor. Based on the log curve, the coal structural type of the No. 3 coal seam was identified, with the thicknesses of the coal body under different types of damage being marked off in each borehole. A damage index of the coal structure (DV) was also proposed, and the DV indexes for all boreholes were calculated. The coal and gas outburst risks in the research area were comprehensively evaluated and predicted through a superposition analysis of the spatial distribution states of three indexes, namely: ground stress, coal structure damage degree, and coal seam gas content. The results show that the equivalent stress of the No. 3 coal seam floor is usually within the range of 9–26 MPa. The high-stress zone presents a strip distribution along the northeast–southwest (NE–SW) direction. The distribution of ground stress is mainly subject to the folds and buried depth of the coal seam. The distribution range where the damage degree of the coal structure falls under Types II and III is DV ≥ 22. The gas outburst risk in the mid-southern and northeastern parts of the research area is high, whereas that in the mid-western part is low. The zones with a high and low degrees of gas outburst risks are all mainly present as strips in the NE–SW direction. The gas outburst risk in the northwest and southeast is moderate. The research results can provide guidance for gas control in non-mining areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".