Numerical Modeling for Excavation Stability: Comparing 2D and 3D Approaches in Underground Mining
Bibliographic record
Abstract
Development headings such as tunnels, ramps, and access are crucial infrastructure components for efficient ore extraction in underground mining operations.Creating these openings, governed by various geological and operational parameters, necessitates careful planning and assessment to ensure the stability and integrity of the excavations.The stability of underground structures is primarily influenced by several factors, including rock mass quality, inducing stress, the depth of the excavation, and the excavation methods applied.These factors are critical in determining the risk of collapse, deformation, or failure, which can significantly impact safety and operational efficiency.To enhance the stability of this excavation, 2D and 3D numerical models (FEM) and field investigations were compared to highlight the deformation around the excavation at varying depths.The numerical results revealed that 3D geomechanical modelling is required to create realistic models in complex geological conditions and under varying depths.However, the 2D geomechanical model can be used in very shallow 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".