Numerical modeling of destress blasting for strata separation
Bibliographic record
Abstract
Destress blasting (DB) implemented along the perimeter of safety pillars is a special application of destressing in coal longwall mining. The goal is to separate relatively more deformed mined areas from safety pillars, such as shaft pillars or cross-cut pillars, to reduce the transfer of high stresses to the protective pillar. This case study aims to numerically simulate selected destress blasts in the Czech part of the Upper Silesian Coal Basin and examine its impact on stress transfer to the safety pillar area. To separate the area between the protective pillar and the longwall (LW), two fans of five 93-mm blast holes (length of 93–100 m) were drilled from the gate roads into the overburden strata. Each set of blast holes was fired separately in two stages without time delay. The explosive charge (gelatin-type of explosive) of each stage is 3450 kg. The two DB stages were fired when the longwall face was approximately 158 m and 152 m away from the blast. A 3D mine-wide model is built and validated with in situ stress measured with hydrofracturing. Mining and destressing in three 5-m thick coal seams are simulated in the region. Numerical modeling of DB is successfully conducted using a rock fragmentation factor α of 0.05 and a stress reduction/dissipation factor β of 0.95. Buffering of transfer of additional stress from the mining area into the safety pillar is evaluated by comparison of yielding volume before and after DB. It is shown that yielding volume drops after DB by nearly 80% in the area of the destressing panel and near the safety shaft pillar.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".