Tunnel support in weak rocks using self-fastening rock bolts SZA
Bibliographic record
Abstract
The article considers the issue of ensuring stability of mine tunnels in weak rocks using the reinforced combined support on the basis of self-fastening rock bolts (SZA) in Artemyevsk Mine of Vostoktsvetmet. The experience of Australian and Canadian mines show that support of mine tunnels in heavily deformable and rockburst-hazardous rocks should possess high energy absorption capacity, i.e., the support must be strong enough to withstand high loads, and at the same time flexible enough to permit a slight displacement of the walls of the mine. Aiming to estimate load-bearing capacity of concrete lining, it was decided to estimate wave impact of blasting (seismic vibration) expressed in terms of explosion output energy. The results of the full-scale trials show that the combination support technology in weak rocks using self-fastening friction-type rock bolts (SZA model) and MasterRoc STS 1510 shotcrete ensures stability of surfaces in tunnels and is applicable in Artemyevsk mine without signifi cant change in the list of available drilling, rockbolting and shotcreting machines, which favors transition to the described design of support.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".