Effect of Rib Pillar Extraction on the Surrounding Rock Mass with Large Diameter Blasthole Stoping as Method of Extraction
Bibliographic record
Abstract
Large scale production methods always pose a serious threat to the natural pillars left intact in underground metalliferrous mines.Rib pillar extraction in underground metal mines is a complex process that requires careful consideration of geo-mechanical factors to ensure stability and safety.The stability of rib pillars is influenced by various parameters, including mining methods, rock mass characteristics, and extraction sequences.Extraction of rib pillar between mined out stopes plays a crucial role in redistribution of stresses around excavated stopes as well as the natural pillars which maintains the stability of the underground structures.Effective design and optimization, often involving numerical modelling techniques, are essential to ensure the safety and efficiency of underground mining operations.The present study focuses on three-dimensional finite element analyses to analyze the behaviour of the surrounding rock mass subjected to rib pillar extraction in an underground copper mine.A remnant vertical pillar of 3 m is left intact on either side of the rib pillar and the rest rock mass of 14 m thickness is extracted.A total of 5 different sequence of extraction have been considered with elastic constitutive material model.Based on the results obtained from the numerical modelling simulation, some useful conclusions have been inferred for the barrier crown pillar, crown pillar between main levels and 3 m remnant pillars.
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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 | 0.000 | 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) | 0.001 | 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".