Experimental Investigation on the Influence of Temperature on Coal and Gas Outbursts
Bibliographic record
Abstract
With the increasing mining depth, the dynamic disaster of coal and gas outbursts in coal mines has become increasingly prominent, and the bursting liability of coal and rock mass in deep coal seam mining is a necessary condition for the occurrence of rock burst and an important index to measure the failure of coal and rock mass. Thermal damage leads to rock instability and failure, which seriously influences the safe and efficient operation of coal mines. To investigate the effect of thermal damage on the bursting liability of deep coals, the burst tendency index of standard coal was measured after subjecting it to thermal damage at different temperatures. The effects of different thermal damage temperatures on the uniaxial compressive strength index, dynamic failure duration, stiffness ratio index, effective impact energy index, residual energy index change rate, and impact energy velocity of the coal and the influence of the post-peak failure mode of the coal were evaluated. The results revealed that the uniaxial compressive strength of the coal generally decreased with increasing thermal damage temperature. At temperatures above 200 °C, the strength significantly decreased. The comprehensive impact property index indicated that, with increasing thermal impact temperature, the burst tendency first increased up to the peak value at 200 °C and then gradually decreased. With the increase in the thermal damage temperature, the burst tendency decreased and disappeared in the temperature range of 250–300 °C, and the failure mode of the coal changed from brittle failure to brittle plastic failure, and finally ductile failure. The influence of thermal damage on coal bursting liability is studied, which provides a theoretical basis for preventing and controlling coal impact ground pressure hazards.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".